Code | Title | Points |
---|---|---|
Linear Algebra Requirement: Select one of the following courses: | ||
COMPUTATIONAL LINEAR ALGEBRA (recommended) | ||
LINEAR ALGEBRA | ||
Linear Algebra and Probability | ||
Honors Linear Algebra | ||
INTRO TO APPLIED MATHEMATICS | ||
APPLIED MATH I: LINEAR ALGEBRA |
Code | Title | Points |
---|---|---|
Probability / Statistics Requirement: Select one of the following courses: | ||
Linear Algebra and Probability | ||
PROBABILITY FOR ENGINEERS | ||
CALC-BASED INTRO TO STATISTICS | ||
INTRODUCTION TO PROBABILITY AND STATISTICS | ||
NOTE: Math 2015 Linear Algebra and Probability may simultaneously satisfy both linear algebra and probability requirements without the need to take additional classes thus reducing the total number of points required. |
Code | Title | Points |
---|---|---|
Recommended (3-4 points) | ||
INTRO TO COMP FOR ENG/APP SCI (recommended but not required) | ||
or | COMPUTING IN CONTEXT |
Code | Title | Points |
---|---|---|
First Year | ||
Introduction to Computer Science and Programming in Java | ||
or COMS W1007 | ||
Sophomore Year | ||
Data Structures in Java | ||
or | HONORS DATA STRUCTURES & ALGOL | |
ADVANCED PROGRAMMING | ||
DISCRETE MATHEMATICS | ||
Junior and Senior Year | ||
Complete the remaining required core courses: | ||
COMPUTER SCIENCE THEORY | ||
FUNDAMENTALS OF COMPUTER SYSTS |
Select three from the following list:
Code | Title | Points |
---|---|---|
INTRODUCTION TO DATABASES | ||
FUND-LARGE-SCALE DIST SYSTEMS | ||
PROGRAMMING LANG & TRANSLATORS | ||
OPERATING SYSTEMS I | ||
COMPUTER NETWORKS | ||
Engineering Software-as-a-Service | ||
ADVANCED SOFTWARE ENGINEERING | ||
COMPUTER GRAPHICS | ||
COMPUTER ANIMATION | ||
USER INTERFACE DESIGN | ||
SECURITY I | ||
ANALYSIS OF ALGORITHMS I | ||
INTRO-COMPUTATIONAL COMPLEXITY | ||
ARTIFICIAL INTELLIGENCE | ||
NATURAL LANGUAGE PROCESSING | ||
Computer Vision I: First Principles | ||
COMPUTATIONAL ASPECTS OF ROBOTICS | ||
COMPUTATIONAL GENOMICS | ||
MACHINE LEARNING | ||
COMPUTER ARCHITECTURE | ||
SYSTEM-ON-CHIP PLATFORMS |
Any three COMS courses or jointly offered computer science courses such as CSXX or XXCS course that are worth at least 3 points and are at the 3000 level or above. This includes 3000-level courses offered by Barnard CS.
Note: No more than 6 points of project/thesis courses (COMS W3902, W3998, W4901) can count toward the major. COMS W3999 Fieldwork cannot be used as a CS Elective.
No more than one course from each set below may be applied towards the computer science major:
IEOR E3658, STAT UN1201, MATH UN2015
MATH UN2015, MATH UN2010, APAM E3101, COMS W3251
COMS W4771, COMS W4721
For a description of the joint major in computer science—mathematics, see the Mathematics section in this bulletin.
For a description of the joint major in mathematics—computer science, see the Mathematics section in this catalog.
The major in information science requires a minimum of 33 points, including a core requirement of five courses. Adjustments were made to the course lists below in March 2022.
The elective courses must be chosen with a faculty adviser to focus on the modeling and use of information within the context of a disciplinary theme. After discussing potential selections, students prepare a proposal of study that must be approved by the faculty adviser. In all cases, the six courses must be at the 3000 level or above, with at least three courses chosen from computer science. Following are some example programs. For more examples or templates for the program proposal, see a faculty adviser.
Note: In most cases, additional courses will be necessary as prerequisites in order to take some of the elective courses. This will depend on the student's proposed program of study.
Code | Title | Points |
---|---|---|
Introduction to Information Science | ||
Computing in Context | ||
Introduction to Computer Science and Programming in Java | ||
Clean Object-Oriented Design | ||
Data Structures in Java | ||
INTRODUCTION TO PROBABILITY AND STATISTICS |
Following are some suggested programs of instruction:
Students may focus on how humans use technology and how technology has changed society.
The requirements include:
Code | Title | Points |
---|---|---|
INTRODUCTION TO DATABASES | ||
USER INTERFACE DESIGN | ||
ARTIFICIAL INTELLIGENCE | ||
COMPUTERS AND SOCIETY | ||
METHODS FOR SOCIAL RESEARCH | ||
SEMINAR - PROBLEMS OF LAW & SOCIETY |
Students may focus on understanding information modeling together with existing and emerging needs in economics and finance as well as algorithms and systems to address those needs.
Code | Title | Points |
---|---|---|
INTRODUCTION TO DATABASES | ||
ARTIFICIAL INTELLIGENCE | ||
MACHINE LEARNING | ||
INTRODUCTION TO ECONOMETRICS | ||
FINANCIAL ECONOMICS | ||
MONEY AND BANKING |
Students may focus on understanding information modeling together with existing and emerging needs in health sciences, as well as algorithms and systems to address those needs.
Code | Title | Points |
---|---|---|
INTRODUCTION TO DATABASES | ||
USER INTERFACE DESIGN | ||
ARTIFICIAL INTELLIGENCE | ||
BINF G4001 | ||
Bioinformatics of Gene Expression | ||
ECBM E3060/E4060 |
In response to the ever-growing importance of "big data" in scientific and policy endeavors, the last few years have seen explosive growth in theory, methods, and applications at the interface between computer science and statistics. The statistics and computer science departments have responded with a joint major that emphasizes the interface between the disciplines.
Code | Title | Points |
---|---|---|
Prerequisites (15 points) | ||
CALCULUS I | ||
CALCULUS II | ||
CALCULUS III | ||
LINEAR ALGEBRA | ||
This introductory Statistics course: | ||
CALC-BASED INTRO TO STATISTICS | ||
Statistics (12 points) | ||
PROBABILITY THEORY | ||
STATISTICAL INFERENCE | ||
LINEAR REGRESSION MODELS | ||
STATISTICAL MACHINE LEARNING | ||
Machine Learning | ||
Computer Science (12 points) | ||
Select one of the following courses: | ||
Introduction to Computer Science and Programming in Java | ||
Introduction to Computer Science and Programming in MATLAB | ||
COMS W1007 | ||
INTRO TO COMP FOR ENG/APP SCI | ||
Select one of the following courses: | ||
Data Structures in Java | ||
ESSENTIAL DATA STRUCTURES | ||
HONORS DATA STRUCTURES & ALGOL | ||
Two required courses: | ||
DISCRETE MATHEMATICS | ||
ANALYSIS OF ALGORITHMS I | ||
Electives (15 points) | ||
Select two of the following courses: | ||
APPLIED MACHINE LEARNING | ||
STAT COMP & INTRO DATA SCIENCE | ||
BAYESIAN STATISTICS | ||
APPLIED DATA SCIENCE | ||
Advanced Machine Learning | ||
Select three of the following courses: | ||
COMPUTER SCIENCE THEORY | ||
INTRODUCTION TO DATABASES | ||
COMS W4130 | ||
INTRO-COMPUTATIONAL COMPLEXITY | ||
INTRO-COMPUTATIONAL LEARN THRY | ||
Any COMS W47xx course EXCEPT W4771 |
Please read Guidelines for all Computer Science Majors and Minors above.
The minor in computer science requires a minimum of 22-24 points, as follows:
Code | Title | Points |
---|---|---|
Introduction to Computer Science and Programming in Java | ||
or COMS W1007 | ||
DISCRETE MATHEMATICS | ||
Data Structures in Java | ||
or | HONORS DATA STRUCTURES & ALGOL | |
ADVANCED PROGRAMMING | ||
COMPUTER SCIENCE THEORY | ||
FUNDAMENTALS OF COMPUTER SYSTS (or any 3 point 4000-level computer science course) | ||
Select one of the following courses: | ||
LINEAR ALGEBRA | ||
INTRO TO APPLIED MATHEMATICS | ||
APPLIED MATH I: LINEAR ALGEBRA | ||
Honors Linear Algebra | ||
INTRODUCTION TO PROBABILITY AND STATISTICS | ||
INTRO PROBABILITY/STATISTICS |
Please read Guidelines for all Computer Science Majors and Concentrators above. Adjustments were made to the course lists below in March 2022.
The concentration in computer science requires a minimum of 22-24 points, as follows:
Code | Title | Points |
---|---|---|
Introduction to Computer Science and Programming in Java | ||
or COMS W1007 | ||
Data Structures in Java | ||
or | HONORS DATA STRUCTURES & ALGOL | |
ADVANCED PROGRAMMING | ||
DISCRETE MATHEMATICS | ||
COMPUTER SCIENCE THEORY | ||
FUNDAMENTALS OF COMPUTER SYSTS (or any 3 point 4000-level computer science course) | ||
Select one of the following courses: | ||
COMPUTATIONAL LINEAR ALGEBRA | ||
LINEAR ALGEBRA | ||
Linear Algebra and Probability | ||
Honors Linear Algebra | ||
INTRO TO APPLIED MATHEMATICS | ||
APPLIED MATH I: LINEAR ALGEBRA | ||
PROBABILITY FOR ENGINEERS | ||
CALC-BASED INTRO TO STATISTICS | ||
INTRODUCTION TO PROBABILITY AND STATISTICS |
COMS W1001 Introduction to Information Science. 3 points .
Basic introduction to concepts and skills in Information Sciences: human-computer interfaces, representing information digitally, organizing and searching information on the internet, principles of algorithmic problem solving, introduction to database concepts, and introduction to programming in Python.
COMS W1002 COMPUTING IN CONTEXT. 4.00 points .
CC/GS: Partial Fulfillment of Science Requirement
Introduction to elementary computing concepts and Python programming with domain-specific applications. Shared CS concepts and Python programming lectures with track-specific sections. Track themes will vary but may include computing for the social sciences, computing for economics and finance, digital humanities, and more. Intended for nonmajors. Students may only receive credit for one of ENGI E1006 or COMS W1002
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 1002 | 001/11915 | T Th 1:10pm - 2:25pm Room TBA | Adam Cannon | 4.00 | 70/160 |
COMS 1002 | 002/11916 | T Th 1:10pm - 2:25pm Room TBA | Adam Cannon | 4.00 | 15/60 |
COMS 1002 | 003/11917 | T Th 2:40pm - 3:55pm Room TBA | Adam Cannon | 4.00 | 131/300 |
COMS 1002 | 004/11918 | T Th 2:40pm - 3:55pm Room TBA | Adam Cannon | 4.00 | 28/40 |
COMS W1003 INTRO-COMPUT SCI/PROGRAM IN C. 3.00 points .
COMS W1004 Introduction to Computer Science and Programming in Java. 3 points .
A general introduction to computer science for science and engineering students interested in majoring in computer science or engineering. Covers fundamental concepts of computer science, algorithmic problem-solving capabilities, and introductory Java programming skills. Assumes no prior programming background. Columbia University students may receive credit for only one of the following two courses: 1004 or 1005 .
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 1004 | 001/11451 | T Th 11:40am - 12:55pm 417 International Affairs Bldg | Adam Cannon | 3 | 123/398 |
COMS 1004 | 002/12052 | T Th 1:10pm - 2:25pm 417 International Affairs Bldg | Adam Cannon | 3 | 116/398 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 1004 | 001/11919 | M W 2:40pm - 3:55pm Room TBA | Paul Blaer | 3 | 93/320 |
COMS 1004 | 002/11920 | M W 5:40pm - 6:55pm Room TBA | Paul Blaer | 3 | 65/320 |
COMS W1005 Introduction to Computer Science and Programming in MATLAB. 3 points .
A general introduction to computer science concepts, algorithmic problem-solving capabilities, and programming skills in MATLAB. Assumes no prior programming background. Columbia University students may receive credit for only one of the following two courses: W1004 or W1005 .
COMS W1011 INTERMED COMPUTER PROGRAMMING. 3.00 points .
COMS W1012 COMPUTING IN CONTEXT REC. 0.00 points .
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 1012 | 001/11921 | Th 7:10pm - 8:00pm Room TBA | Adam Cannon | 0.00 | 0/40 |
COMS 1012 | 002/11922 | Th 7:10pm - 8:00pm Room TBA | Adam Cannon | 0.00 | 0/40 |
COMS 1012 | 003/11923 | F 10:10am - 11:00am Room TBA | Adam Cannon | 0.00 | 0/40 |
COMS 1012 | 004/11924 | F 2:00pm - 2:50pm Room TBA | Adam Cannon | 0.00 | 0/40 |
COMS 1012 | 005/11925 | Th 7:10pm - 8:00pm Room TBA | Adam Cannon | 0.00 | 0/40 |
COMS 1012 | 006/11926 | Th 7:10pm - 8:00pm Room TBA | Adam Cannon | 0.00 | 0/40 |
COMS 1012 | 007/11927 | F 9:00am - 9:50am Room TBA | Adam Cannon | 0.00 | 0/40 |
COMS 1012 | 008/11928 | Th 7:10pm - 8:00pm Room TBA | Adam Cannon | 0.00 | 0/30 |
COMS 1012 | 009/11929 | F 10:10am - 11:00am Room TBA | Adam Cannon | 0.00 | 0/30 |
COMS 1012 | 010/11930 | Th 7:10pm - 8:00pm Room TBA | Adam Cannon | 0.00 | 0/30 |
COMS 1012 | 011/11931 | F 11:00am - 11:50am Room TBA | Adam Cannon | 0.00 | 0/30 |
COMS W1103 HONORS INTRO COMPUTER SCIENCE. 3.00 points .
COMS W1404 EMERGING SCHOLARS PROG SEMINAR. 1.00 point .
Pass/Fail only.
Prerequisites: the instructor's permission. Corequisites: COMS W1002 or COMS W1004 or COMS W1007 Corequisites: COMS W1004 ,COMS W1007, COMS W1002 Peer-led weekly seminar intended for first and second year undergraduates considering a major in Computer Science. Pass/fail only. May not be used towards satisfying the major or SEAS credit requirements
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 1404 | 001/12053 | F 8:40am - 9:55am 502 Northwest Corner | Adam Cannon | 1.00 | 6/16 |
COMS 1404 | 002/12054 | F 10:10am - 11:25am 502 Northwest Corner | Adam Cannon | 1.00 | 3/16 |
COMS 1404 | 003/12055 | F 11:40am - 12:55pm 502 Northwest Corner | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 004/12056 | F 1:10pm - 2:25pm 502 Northwest Corner | Adam Cannon | 1.00 | 4/16 |
COMS 1404 | 005/12057 | F 2:40pm - 3:55pm 502 Northwest Corner | Adam Cannon | 1.00 | 6/16 |
COMS 1404 | 006/12058 | F 4:10pm - 5:25pm 502 Northwest Corner | Adam Cannon | 1.00 | 3/16 |
COMS 1404 | 007/12059 | F 9:30am - 10:45am 253 Engineering Terrace | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 008/12061 | F 11:00am - 12:15pm 253 Engineering Terrace | Adam Cannon | 1.00 | 5/16 |
COMS 1404 | 009/12063 | F 12:30pm - 1:45pm 253 Engineering Terrace | Adam Cannon | 1.00 | 9/16 |
COMS 1404 | 010/12064 | F 2:00pm - 3:15pm 253 Engineering Terrace | Adam Cannon | 1.00 | 3/16 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 1404 | 001/11996 | F 8:40am - 9:55am Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 002/11997 | F 10:10am - 11:25am Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 003/11998 | F 11:40am - 12:55pm Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 004/11999 | F 1:10pm - 2:25pm Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 005/12000 | F 2:40pm - 3:55pm Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 006/12001 | F 4:10pm - 5:25pm Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 007/12002 | F 9:30am - 10:45am Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 008/12003 | F 11:00am - 12:15pm Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 009/12004 | F 12:30pm - 1:45pm Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS 1404 | 010/12005 | F 2:00pm - 3:15pm Room TBA | Adam Cannon | 1.00 | 0/16 |
COMS W3011 INTERMED COMPUTER PROGRAMMING. 3.00 points .
COMS W3101 PROGRAMMING LANGUAGES. 1.00 point .
Prerequisites: Fluency in at least one programming language. Introduction to a programming language. Each section is devoted to a specific language. Intended only for those who are already fluent in at least one programming language. Sections may meet for one hour per week for the whole term, for three hours per week for the first third of the term, or for two hours per week for the first six weeks. May be repeated for credit if different languages are involved
COMS W3102 DEVELOPMENT TECHNOLOGY. 1.00-2.00 points .
Lect: 2. Lab: 0-2.
Prerequisites: Fluency in at least one programming language. Introduction to software development tools and environments. Each section devoted to a specific tool or environment. One-point sections meet for two hours each week for half a semester, and two point sections include an additional two-hour lab
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 3102 | 001/12065 | F 6:10pm - 8:00pm 451 Computer Science Bldg | Shoaib Ahamed | 1.00-2.00 | 62/70 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 3102 | 001/13801 | F 10:10am - 12:00pm Room TBA | Shoaib Ahamed | 1.00-2.00 | 74/100 |
COMS W3107 Clean Object-Oriented Design. 3.00 points .
Prerequisites: Intro to Computer Science/Programming in Java (COMS W1004) or instructor’s permission. May not take for credit if already received credit for COMS W1007.
Prerequisites: see notes re: points A course in designing, documenting, coding, and testing robust computer software, according to object-oriented design patterns and clean coding practices. Taught in Java.Object-oriented design principles include: use cases; CRC; UML; javadoc; patterns (adapter, builder, command, composite, decorator, facade, factory, iterator, lazy evaluation, observer, singleton, strategy, template, visitor); design by contract; loop invariants; interfaces and inheritance hierarchies; anonymous classes and null objects; graphical widgets; events and listeners; Java's Object class; generic types; reflection; timers, threads, and locks
COMS W3123 ASSEMBLY LANG AND COMPUT LOGIC. 3.00 points .
COMS W3132 Intermediate Computing in Python. 4.00 points .
Essential data structures and algorithms in Python with practical software development skills, applications in a variety of areas including biology, natural language processing, data science and others
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 3132 | 001/15110 | F 1:10pm - 3:40pm 413 Kent Hall | Jan Janak | 4.00 | 60/60 |
COMS W3134 Data Structures in Java. 3 points .
Prerequisites: ( COMS W1004 ) or knowledge of Java.
Data types and structures: arrays, stacks, singly and doubly linked lists, queues, trees, sets, and graphs. Programming techniques for processing such structures: sorting and searching, hashing, garbage collection. Storage management. Rudiments of the analysis of algorithms. Taught in Java. Note: Due to significant overlap, students may receive credit for only one of the following three courses: COMS W3134 , COMS W3136 , COMS W3137 .
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 3134 | 001/12067 | M W 4:10pm - 5:25pm 301 Uris Hall | Brian Borowski | 3 | 227/250 |
COMS 3134 | 002/12068 | M W 5:40pm - 6:55pm 301 Uris Hall | Brian Borowski | 3 | 144/250 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 3134 | 001/11932 | M W 4:10pm - 5:25pm Room TBA | Brian Borowski | 3 | 144/200 |
COMS 3134 | 002/11933 | M W 5:40pm - 6:55pm Room TBA | Brian Borowski | 3 | 82/200 |
COMS W3136 ESSENTIAL DATA STRUCTURES. 4.00 points .
Prerequisites: ( COMS W1004 ) or ( COMS W1005 ) or (COMS W1007) or ( ENGI E1006 ) A second programming course intended for nonmajors with at least one semester of introductory programming experience. Basic elements of programming in C and C , arraybased data structures, heaps, linked lists, C programming in UNIX environment, object-oriented programming in C , trees, graphs, generic programming, hash tables. Due to significant overlap, students may only receive credit for either COMS W3134 , W3136 , or W3137
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 3136 | 001/15424 | T Th 5:40pm - 6:55pm Room TBA | Timothy Paine | 4.00 | 16/65 |
COMS W3137 HONORS DATA STRUCTURES & ALGOL. 4.00 points .
Prerequisites: ( COMS W1004 ) or (COMS W1007) Corequisites: COMS W3203 An honors introduction to data types and structures: arrays, stacks, singly and doubly linked lists, queues, trees, sets, and graphs. Programming techniques for processing such structures: sorting and searching, hashing, garbage collection. Storage management. Design and analysis of algorithms. Taught in Java. Note: Due to significant overlap, students may receive credit for only one of the following three courses: COMS W3134 , W3136 , or W3137
COMS W3157 ADVANCED PROGRAMMING. 4.00 points .
Prerequisites: ( COMS W3134 ) or ( COMS W3137 ) C programming language and Unix systems programming. Also covers Git, Make, TCP/IP networking basics, C fundamentals
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 3157 | 001/12069 | T Th 4:10pm - 5:25pm 417 International Affairs Bldg | Jae Lee | 4.00 | 295/398 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 3157 | 001/11934 | T Th 4:10pm - 5:25pm Room TBA | Jae Lee | 4.00 | 332/398 |
COMS W3202 FINITE MATHEMATICS. 3.00 points .
COMS W3203 DISCRETE MATHEMATICS. 4.00 points .
Prerequisites: Any introductory course in computer programming. Logic and formal proofs, sequences and summation, mathematical induction, binomial coefficients, elements of finite probability, recurrence relations, equivalence relations and partial orderings, and topics in graph theory (including isomorphism, traversability, planarity, and colorings)
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 3203 | 001/12070 | T Th 10:10am - 11:25am 301 Uris Hall | Ansaf Salleb-Aouissi | 4.00 | 215/200 |
COMS 3203 | 002/12071 | T Th 11:40am - 12:55pm 301 Uris Hall | Ansaf Salleb-Aouissi | 4.00 | 207/200 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 3203 | 001/11935 | M W 4:10pm - 5:25pm Room TBA | Tony Dear | 4.00 | 151/270 |
COMS W3210 Scientific Computation. 3 points .
Prerequisites: two terms of calculus.
Introduction to computation on digital computers. Design and analysis of numerical algorithms. Numerical solution of equations, integration, recurrences, chaos, differential equations. Introduction to Monte Carlo methods. Properties of floating point arithmetic. Applications to weather prediction, computational finance, computational science, and computational engineering.
COMS W3251 COMPUTATIONAL LINEAR ALGEBRA. 4.00 points .
COMS W3261 COMPUTER SCIENCE THEORY. 3.00 points .
Prerequisites: ( COMS W3203 ) Corequisites: COMS W3134 , COMS W3136 , COMS W3137 Regular languages: deterministic and non-deterministic finite automata, regular expressions. Context-free languages: context-free grammars, push-down automata. Turing machines, the Chomsky hierarchy, and the Church-Turing thesis. Introduction to Complexity Theory and NP-Completeness
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 3261 | 001/12072 | M W 2:40pm - 3:55pm 417 International Affairs Bldg | Josh Alman | 3.00 | 130/150 |
COMS 3261 | 022/12073 | T Th 11:40am - 12:55pm 501 Northwest Corner | Mihalis Yannakakis | 3.00 | 152/160 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 3261 | 001/11936 | T Th 8:40am - 9:55am Room TBA | Tal Malkin | 3.00 | 105/105 |
COMS 3261 | 002/11937 | T Th 10:10am - 11:25am Room TBA | Tal Malkin | 3.00 | 105/105 |
COMS W3410 COMPUTERS AND SOCIETY. 3.00 points .
Broader impact of computers. Social networks and privacy. Employment, intellectual property, and the media. Science and engineering ethics. Suitable for nonmajors
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 3410 | 001/11938 | W 4:10pm - 6:40pm Room TBA | Ronald Baecker | 3.00 | 60/60 |
COMS E3899 Research Training. 0.00 points .
Research training course. Recommended in preparation for laboratory related research
COMS W3902 UNDERGRADUATE THESIS. 0.00-6.00 points .
Prerequisites: Agreement by a faculty member to serve as thesis adviser. An independent theoretical or experimental investigation by an undergraduate major of an appropriate problem in computer science carried out under the supervision of a faculty member. A formal written report is mandatory and an oral presentation may also be required. May be taken over more than one term, in which case the grade is deferred until all 6 points have been completed. Consult the department for section assignment
COMS W3995 Special Topics in Computer Science. 3 points .
Prerequisites: the instructor's permission.
Consult the department for section assignment. Special topics arranged as the need and availability arise. Topics are usually offered on a one-time basis. Since the content of this course changes each time it is offered, it may be repeated for credit.
COMS W3998 UNDERGRAD PROJECTS IN COMPUTER SCIENCE. 1.00-3.00 points .
Prerequisites: Approval by a faculty member who agrees to supervise the work. Independent project involving laboratory work, computer programming, analytical investigation, or engineering design. May be repeated for credit. Consult the department for section assignment
COMS W3999 FIELDWORK. 1.00 point .
May be repeated for credit, but no more than 3 total points may be used toward the 128-credit degree requirement. Final report and letter of evaluation required. May not be used as a technical or non-technical elective. May not be taken for pass/fail credit or audited
COMS E3999 Fieldwork. 1 point .
Prerequisites: Obtained internship and approval from faculty advisor.
May be repeated for credit, but no more than 3 total points may be used toward the 128-credit degree requirement. Only for SEAS computer science undergraduate students who include relevant off-campus work experience as part of their approved program of study. Final report and letter of evaluation required. May not be used as a technical or non-technical elective. May not be taken for pass/fail credit or audited.
COMS W4111 INTRODUCTION TO DATABASES. 3.00 points .
CC/GS: Partial Fulfillment of Science Requirement Prerequisites: COMS W3134, COMS W3136, or COMS W3137; or the instructor's permission.
Prerequisites: ( COMS W3134 ) or ( COMS W3136 ) or ( COMS W3137 ) or The fundamentals of database design and application development using databases: entity-relationship modeling, logical design of relational databases, relational data definition and manipulation languages, SQL, XML, query processing, physical database tuning, transaction processing, security. Programming projects are required
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4111 | 001/12074 | M W 2:40pm - 3:55pm 309 Havemeyer Hall | Kenneth Ross | 3.00 | 126/200 |
COMS 4111 | 002/12075 | F 10:10am - 12:40pm 417 International Affairs Bldg | Donald Ferguson | 3.00 | 398/398 |
COMS 4111 | V02/20370 | | Donald Ferguson | 3.00 | 18/99 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4111 | 001/11939 | T Th 10:10am - 11:25am Room TBA | Luis Gravano | 3.00 | 85/150 |
COMS 4111 | 002/11940 | T Th 8:40am - 9:55am Room TBA | Eugene Wu | 3.00 | 15/150 |
COMS 4111 | 003/11941 | F 10:10am - 12:40pm Room TBA | Donald Ferguson | 3.00 | 125/200 |
COMS W4112 DATABASE SYSTEM IMPLEMENTATION. 3.00 points .
Prerequisites: ( COMS W4111 ) and fluency in Java or C++. CSEE W3827 is recommended. The principles and practice of building large-scale database management systems. Storage methods and indexing, query processing and optimization, materialized views, transaction processing and recovery, object-relational databases, parallel and distributed databases, performance considerations. Programming projects are required
COMS W4113 FUND-LARGE-SCALE DIST SYSTEMS. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) and ( COMS W3157 or COMS W4118 or CSEE W4119 ) Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) and ( COMS W3157 or COMS W4118 or CSEE W4119 ) Design and implementation of large-scale distributed and cloud systems. Teaches abstractions, design and implementation techniques that enable the building of fast, scalable, fault-tolerant distributed systems. Topics include distributed communication models (e.g. sockets, remote procedure calls, distributed shared memory), distributed synchronization (clock synchronization, logical clocks, distributed mutex), distributed file systems, replication, consistency models, fault tolerance, distributed transactions, agreement and commitment, Paxos-based consensus, MapReduce infrastructures, scalable distributed databases. Combines concepts and algorithms with descriptions of real-world implementations at Google, Facebook, Yahoo, Microsoft, LinkedIn, etc
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4113 | 001/11942 | F 10:10am - 12:40pm Room TBA | Roxana Geambasu | 3.00 | 100/110 |
COMS 4113 | V01/17521 | | Roxana Geambasu | 3.00 | 0/99 |
COMS E4115 PROGRAMMING LANG & TRANSL. 3.00 points .
COMS W4115 PROGRAMMING LANG & TRANSLATORS. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) and ( COMS W3261 ) and ( CSEE W3827 ) or equivalent, or the instructor's permission. Modern programming languages and compiler design. Imperative, object-oriented, declarative, functional, and scripting languages. Language syntax, control structures, data types, procedures and parameters, binding, scope, run-time organization, and exception handling. Implementation of language translation tools including compilers and interpreters. Lexical, syntactic and semantic analysis; code generation; introduction to code optimization. Teams implement a language and its compiler
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4115 | 001/12077 | M W 4:10pm - 5:25pm 501 Schermerhorn Hall | Ronghui Gu | 3.00 | 72/120 |
COMS 4115 | V01/15375 | | Ronghui Gu | 3.00 | 11/99 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4115 | 001/11943 | T Th 11:40am - 12:55pm Room TBA | Baishakhi Ray | 3.00 | 37/100 |
COMS W4118 OPERATING SYSTEMS I. 3.00 points .
Prerequisites: ( CSEE W3827 ) and knowledge of C and programming tools as covered in COMS W3136 , W3157 , or W3101, or the instructor's permission. Design and implementation of operating systems. Topics include process management, process synchronization and interprocess communication, memory management, virtual memory, interrupt handling, processor scheduling, device management, I/O, and file systems. Case study of the UNIX operating system. A programming project is required
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4118 | 001/12079 | T Th 4:10pm - 5:25pm 501 Northwest Corner | Kostis Kaffes | 3.00 | 88/160 |
COMS 4118 | V01/18798 | | Kostis Kaffes | 3.00 | 4/99 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4118 | 001/11944 | T Th 4:10pm - 5:25pm Room TBA | Jason Nieh | 3.00 | 84/160 |
COMS 4118 | V01/17522 | | Jason Nieh | 3.00 | 0/99 |
COMS W4119 COMPUTER NETWORKS. 3.00 points .
Introduction to computer networks and the technical foundations of the internet, including applications, protocols, local area networks, algorithms for routing and congestion control, security, elementary performance evaluation. Several written and programming assignments required
COMS W4121 COMPUTER SYSTEMS FOR DATA SCIENCE. 3.00 points .
Prerequisites: background in Computer System Organization and good working knowledge of C/C++ Corequisites: CSOR W4246 , STAT GU4203 An introduction to computer architecture and distributed systems with an emphasis on warehouse scale computing systems. Topics will include fundamental tradeoffs in computer systems, hardware and software techniques for exploiting instruction-level parallelism, data-level parallelism and task level parallelism, scheduling, caching, prefetching, network and memory architecture, latency and throughput optimizations, specialization, and an introduction to programming data center computers
COMS W4137 From Algorithmic Thinking to Development. 3.00 points .
Algorithmic problem-solving and coding skills needed to devise solutions to interview questions for software engineering positions. Solutions are implemented in Python, Java, C, and C . Approaches include brute-force, hashing, sorting, transform-and-conquer, greedy, and dynamic programming. Focus on experimentation and team work
COMS W4152 Engineering Software-as-a-Service. 3.00 points .
Modern software engineering concepts and practices including topics such as Software-as-a-Service, Service-oriented Architecture, Agile Development, Behavior-driven Development, Ruby on Rails, and Dev/ops
COMS W4153 Cloud Computing. 3.00 points .
Software engineering skills necessary for developing cloud computing and software-as-a-service applications, covering topics such as service-oriented architectures, message-driven applications, and platform integration. Includes theoretical study, practical application, and collaborative project work
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4153 | 001/14010 | F 1:10pm - 3:40pm Room TBA | Donald Ferguson | 3.00 | 151/200 |
COMS W4156 ADVANCED SOFTWARE ENGINEERING. 3.00 points .
Prerequisites: ( COMS W3157 ) or equivalent. Software lifecycle using frameworks, libraries and services. Major emphasis on software testing. Centers on a team project
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4156 | 001/11945 | T Th 10:10am - 11:25am Room TBA | Gail Kaiser | 3.00 | 52/120 |
COMS W4160 COMPUTER GRAPHICS. 3.00 points .
Prerequisites: ( COMS W3134 ) or ( COMS W3136 ) or ( COMS W3137 ) COMS W4156 is recommended. Strong programming background and some mathematical familiarity including linear algebra is required. Introduction to computer graphics. Topics include 3D viewing and projections, geometric modeling using spline curves, graphics systems such as OpenGL, lighting and shading, and global illumination. Significant implementation is required: the final project involves writing an interactive 3D video game in OpenGL
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4160 | 001/13865 | T Th 7:10pm - 8:25pm 451 Computer Science Bldg | Hadi Fadaifard | 3.00 | 64/75 |
COMS W4162 Advanced Computer Graphics. 3 points .
Prerequisites: ( COMS W4160 ) or equivalent, or the instructor's permission.
A second course in computer graphics covering more advanced topics including image and signal processing, geometric modeling with meshes, advanced image synthesis including ray tracing and global illumination, and other topics as time permits. Emphasis will be placed both on implementation of systems and important mathematical and geometric concepts such as Fourier analysis, mesh algorithms and subdivision, and Monte Carlo sampling for rendering. Note: Course will be taught every two years.
COMS W4165 COMPUT TECHNIQUES-PIXEL PROCSS. 3.00 points .
An intensive introduction to image processing - digital filtering theory, image enhancement, image reconstruction, antialiasing, warping, and the state of the art in special effects. Topics from the basis of high-quality rendering in computer graphics and of low-level processing for computer vision, remote sensing, and medical imaging. Emphasizes computational techniques for implementing useful image-processing functions
COMS W4167 COMPUTER ANIMATION. 3.00 points .
Prerequisites: Multivariable calculus, linear algebra, C++ programming proficiency. COMS W4156 recommended.
Theory and practice of physics-based animation algorithms, including animated clothing, hair, smoke, water, collisions, impact, and kitchen sinks. Topics covered: Integration of ordinary differential equations, formulation of physical models, treatment of discontinuities including collisions/contact, animation control, constrained Lagrangian Mechanics, friction/dissipation, continuum mechanics, finite elements, rigid bodies, thin shells, discretization of Navier-Stokes equations. General education requirement: quantitative and deductive reasoning (QUA).
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4167 | 001/12080 | T Th 4:10pm - 5:25pm 451 Computer Science Bldg | Changxi Zheng | 3.00 | 46/75 |
COMS W4170 USER INTERFACE DESIGN. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) Introduction to the theory and practice of computer user interface design, emphasizing the software design of graphical user interfaces. Topics include basic interaction devices and techniques, human factors, interaction styles, dialogue design, and software infrastructure. Design and programming projects are required
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4170 | 001/12081 | M W 1:10pm - 2:25pm 417 International Affairs Bldg | Lydia Chilton | 3.00 | 412/398 |
COMS 4170 | V01/15381 | | Lydia Chilton | 3.00 | 20/20 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4170 | 001/11946 | T Th 1:10pm - 2:25pm Room TBA | Brian Smith | 3.00 | 0/120 |
COMS 4170 | V01/17523 | | Brian Smith | 3.00 | 0/99 |
COMS W4172 3D UI AND AUGMENTED REALITY. 3.00 points .
Prerequisites: ( COMS W4160 ) or ( COMS W4170 ) or the instructor's permission. Design, development, and evaluation of 3D user interfaces. Interaction techniques and metaphors, from desktop to immersive. Selection and manipulation. Travel and navigation. Symbolic, menu, gestural, and multimodal interaction. Dialogue design. 3D software support. 3D interaction devices and displays. Virtual and augmented reality. Tangible user interfaces. Review of relevant 3D math
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4172 | 001/12082 | T Th 1:10pm - 2:25pm 227 Seeley W. Mudd Building | Steven Feiner | 3.00 | 35/45 |
COMS W4181 SECURITY I. 3.00 points .
Not offered during 2023-2024 academic year.
Prerequisites: COMS W3157 or equivalent. Introduction to security. Threat models. Operating system security features. Vulnerabilities and tools. Firewalls, virtual private networks, viruses. Mobile and app security. Usable security. Note: May not earn credit for both W4181 and W4180 or W4187
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4181 | 001/11947 | M W 1:10pm - 2:25pm Room TBA | Suman Jana | 3.00 | 65/60 |
COMS W4182 SECURITY II. 3.00 points .
Prerequisites: COMS W4181 , COMS W4118 , COMS W4119 Advanced security. Centralized, distributed, and cloud system security. Cryptographic protocol design choices. Hardware and software security techniques. Security testing and fuzzing. Blockchain. Human security issues. Note: May not earn credit for both W4182 and W4180 or W4187
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4182 | 001/12083 | F 1:10pm - 3:40pm 1127 Seeley W. Mudd Building | John Koh | 3.00 | 21/40 |
COMS 4182 | V01/15421 | | John Koh | 3.00 | 2/99 |
COMS W4186 MALWARE ANALYSIS&REVERSE ENGINEERING. 3.00 points .
Prerequisites: COMS W3157 or equivalent. COMS W3827 Hands-on analysis of malware. How hackers package and hide malware and viruses to evade analysis. Disassemblers, debuggers, and other tools for reverse engineering. Deep study of Windows Internals and x86 assembly
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4186 | 001/12324 | Th 4:10pm - 6:40pm Room TBA | Michael Sikorski | 3.00 | 40/40 |
COMS W4203 Graph Theory. 3 points .
Prerequisites: ( COMS W3203 )
General introduction to graph theory. Isomorphism testing, algebraic specification, symmetries, spanning trees, traversability, planarity, drawings on higher-order surfaces, colorings, extremal graphs, random graphs, graphical measurement, directed graphs, Burnside-Polya counting, voltage graph theory.
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4203 | 001/20497 | W 7:00pm - 9:30pm 451 Computer Science Bldg | Yihao Zhang | 3 | 24/60 |
COMS W4205 Combinatorial Theory. 3 points .
Lect: 3. Not offered during 2023-2024 academic year.
Prerequisites: ( COMS W3203 ) and course in calculus.
Sequences and recursions, calculus of finite differences and sums, elementary number theory, permutation group structures, binomial coefficients, Stilling numbers, harmonic numbers, generating functions.
COMS W4223 Networks, Crowds, and the Web. 3.00 points .
Introduces fundamental ideas and algorithms on networks of information collected by online services. It covers properties pervasive in large networks, dynamics of individuals that lead to large collective phenomena, mechanisms underlying the web economy, and results and tools informing societal impact of algorithms on privacy, polarization and discrimination
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4223 | 001/15083 | T Th 4:10pm - 5:25pm 833 Seeley W. Mudd Building | Augustin Chaintreau | 3.00 | 69/110 |
COMS 4223 | V01/18856 | | Augustin Chaintreau | 3.00 | 14/99 |
COMS W4231 ANALYSIS OF ALGORITHMS I. 3.00 points .
COMS W4232 Advanced Algorithms. 3.00 points .
Prerequisite: Analysis of Algorithms (COMS W4231).
Prerequisites: see notes re: points Introduces classic and modern algorithmic ideas that are central to many areas of Computer Science. The focus is on most powerful paradigms and techniques of how to design algorithms, and how to measure their efficiency. The intent is to be broad, covering a diversity of algorithmic techniques, rather than be deep. The covered topics have all been implemented and are widely used in industry. Topics include: hashing, sketching/streaming, nearest neighbor search, graph algorithms, spectral graph theory, linear programming, models for large-scale computation, and other related topics
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4232 | 001/12084 | M W 2:40pm - 3:55pm 633 Seeley W. Mudd Building | Alexandr Andoni | 3.00 | 43/100 |
COMS 4232 | V01/15422 | | Alexandr Andoni | 3.00 | 2/99 |
COMS W4236 INTRO-COMPUTATIONAL COMPLEXITY. 3.00 points .
Prerequisites: ( COMS W3261 ) Develops a quantitative theory of the computational difficulty of problems in terms of the resources (e.g. time, space) needed to solve them. Classification of problems into complexity classes, reductions, and completeness. Power and limitations of different modes of computation such as nondeterminism, randomization, interaction, and parallelism
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4236 | 001/11948 | M W 8:40am - 9:55am Room TBA | Xi Chen | 3.00 | 31/50 |
COMS 4236 | V01/17552 | | Xi Chen | 3.00 | 0/99 |
COMS W4241 Numerical Algorithms and Complexity. 3 points .
Prerequisites: Knowledge of a programming language. Some knowledge of scientific computation is desirable.
Modern theory and practice of computation on digital computers. Introduction to concepts of computational complexity. Design and analysis of numerical algorithms. Applications to computational finance, computational science, and computational engineering.
COMS W4242 NUMRCL ALGORTHMS-COMPLEXITY II. 3.00 points .
COMS W4252 INTRO-COMPUTATIONAL LEARN THRY. 3.00 points .
Prerequisites: ( CSOR W4231 ) or ( COMS W4236 ) or COMS W3203 and the instructor's permission, or COMS W3261 and the instructor's permission.
Possibilities and limitations of performing learning by computational agents. Topics include computational models of learning, polynomial time learnability, learning from examples and learning from queries to oracles. Computational and statistical limitations of learning. Applications to Boolean functions, geometric functions, automata.
COMS W4261 INTRO TO CRYPTOGRAPHY. 3.00 points .
Prerequisites: Comfort with basic discrete math and probability. Recommended: COMS W3261 or CSOR W4231 . An introduction to modern cryptography, focusing on the complexity-theoretic foundations of secure computation and communication in adversarial environments; a rigorous approach, based on precise definitions and provably secure protocols. Topics include private and public key encryption schemes, digital signatures, authentication, pseudorandom generators and functions, one-way functions, trapdoor functions, number theory and computational hardness, identification and zero knowledge protocols
COMS W4281 INTRO TO QUANTUM COMPUTING. 3.00 points .
Prerequisites: Knowledge of linear algebra. Prior knowledge of quantum mechanics is not required although helpful.
Introduction to quantum computing. Shor's factoring algorithm, Grover's database search algorithm, the quantum summation algorithm. Relationship between classical and quantum computing. Potential power of quantum computers.
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4281 | 001/11949 | M W 10:10am - 11:25am Room TBA | Henry Yuen | 3.00 | 0/90 |
COMS W4419 INTERNET TECHNOLOGY,ECONOMICS,AND POLICY. 3.00 points .
Technology, economic and policy aspects of the Internet. Summarizes how the Internet works technically, including protocols, standards, radio spectrum, global infrastructure and interconnection. Micro-economics with a focus on media and telecommunication economic concerns, including competition and monopolies, platforms, and behavioral economics. US constitution, freedom of speech, administrative procedures act and regulatory process, universal service, role of FCC. Not a substitute for CSEE4119. Suitable for non-majors. May not be used as a track elective for the computer science major.
COMS W4444 PROGRAMMING & PROBLEM SOLVING. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) and ( CSEE W3827 ) Hands-on introduction to solving open-ended computational problems. Emphasis on creativity, cooperation, and collaboration. Projects spanning a variety of areas within computer science, typically requiring the development of computer programs. Generalization of solutions to broader problems, and specialization of complex problems to make them manageable. Team-oriented projects, student presentations, and in-class participation required
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4444 | 001/11950 | M W 1:10pm - 2:25pm Room TBA | Kenneth Ross | 3.00 | 0/33 |
COMS W4460 PRIN-INNOVATN/ENTREPRENEURSHIP. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) or the instructor's permission. Team project centered course focused on principles of planning, creating, and growing a technology venture. Topics include: identifying and analyzing opportunities created by technology paradigm shifts, designing innovative products, protecting intellectual property, engineering innovative business models
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4460 | 001/12085 | M W 8:40am - 9:55am 415 Schapiro Cepser | William Reinisch | 3.00 | 34/40 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4460 | 001/13626 | F 10:10am - 12:40pm Room TBA | William Reinisch | 3.00 | 30/40 |
COMS W4701 ARTIFICIAL INTELLIGENCE. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) and any course on probability. Prior knowledge of Python is recommended. Prior knowledge of Python is recommended. Provides a broad understanding of the basic techniques for building intelligent computer systems. Topics include state-space problem representations, problem reduction and and-or graphs, game playing and heuristic search, predicate calculus, and resolution theorem proving, AI systems and languages for knowledge representation, machine learning and concept formation and other topics such as natural language processing may be included as time permits
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4701 | 001/12086 | M W 2:40pm - 3:55pm 501 Northwest Corner | Tony Dear | 3.00 | 90/164 |
COMS 4701 | 002/12087 | M W 4:10pm - 5:25pm 501 Northwest Corner | Tony Dear | 3.00 | 102/164 |
COMS 4701 | V01/17158 | | Tony Dear | 3.00 | 8/99 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4701 | 001/11951 | T Th 10:10am - 11:25am Room TBA | Ansaf Salleb-Aouissi | 3.00 | 152/180 |
COMS 4701 | 002/11952 | T Th 11:40am - 12:55pm Room TBA | Ansaf Salleb-Aouissi | 3.00 | 118/180 |
COMS 4701 | V01/17524 | | Ansaf Salleb-Aouissi | 3.00 | 0/99 |
COMS W4705 NATURAL LANGUAGE PROCESSING. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) or the instructor's permission. Computational approaches to natural language generation and understanding. Recommended preparation: some previous or concurrent exposure to AI or Machine Learning. Topics include information extraction, summarization, machine translation, dialogue systems, and emotional speech. Particular attention is given to robust techniques that can handle understanding and generation for the large amounts of text on the Web or in other large corpora. Programming exercises in several of these areas
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4705 | 001/12088 | M W 2:40pm - 3:55pm 451 Computer Science Bldg | Daniel Bauer | 3.00 | 110/110 |
COMS 4705 | 002/12090 | F 10:10am - 12:40pm 301 Pupin Laboratories | Daniel Bauer | 3.00 | 205/272 |
COMS 4705 | V02/15423 | | Daniel Bauer | 3.00 | 18/99 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4705 | 001/11953 | F 10:10am - 12:40pm Room TBA | Daniel Bauer | 3.00 | 105/240 |
COMS 4705 | 002/11954 | M W 4:10pm - 5:25pm Room TBA | Zhou Yu | 3.00 | 58/100 |
COMS 4705 | V01/17525 | | Daniel Bauer | 3.00 | 0/99 |
COMS W4706 Spoken Language Processing. 3 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) or the instructor's permission.
Computational approaches to speech generation and understanding. Topics include speech recognition and understanding, speech analysis for computational linguistics research, and speech synthesis. Speech applications including dialogue systems, data mining, summarization, and translation. Exercises involve data analysis and building a small text-to-speech system.
COMS W4721 MACHINE LEARNING FOR DATA SCI. 3.00 points .
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4721 | 001/12843 | F 1:10pm - 3:40pm 501 Schermerhorn Hall | Nakul Verma, Robert Kramer | 3.00 | 171/189 |
COMS 4721 | V01/16718 | | Nakul Verma | 3.00 | 2/99 |
COMS W4725 Knowledge representation and reasoning. 3 points .
Prerequisites: ( COMS W4701 )
General aspects of knowledge representation (KR). The two fundamental paradigms (semantic networks and frames) and illustrative systems. Topics include hybrid systems, time, action/plans, defaults, abduction, and case-based reasoning. Throughout the course particular attention is paid to design trade-offs between language expressiveness and reasoning complexity, and issues relating to the use of KR systems in larger applications.
COMS W4731 Computer Vision I: First Principles. 3.00 points .
Prerequisites: Fundamentals of calculus, linear algebra, and C programming. Students without any of these prerequisites are advised to contact the instructor prior to taking the course. Introductory course in computer vision. Topics include image formation and optics, image sensing, binary images, image processing and filtering, edge extraction and boundary detection, region growing and segmentation, pattern classification methods, brightness and reflectance, shape from shading and photometric stereo, texture, binocular stereo, optical flow and motion, 2D and 3D object representation, object recognition, vision systems and applications
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4731 | 001/11955 | M W 10:10am - 11:25am 451 Computer Science Bldg | Shree Nayar | 3.00 | 107/100 |
COMS W4732 Computer Vision II: Learning. 3.00 points .
Advanced course in computer vision. Topics include convolutional networks and back-propagation, object and action recognition, self-supervised and few-shot learning, image synthesis and generative models, object tracking, vision and language, vision and audio, 3D representations, interpretability, and bias, ethics, and media deception
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4732 | 001/12091 | F 10:10am - 12:40pm 451 Computer Science Bldg | Carl Vondrick | 3.00 | 109/100 |
COMS 4732 | V01/15424 | | Carl Vondrick | 3.00 | 46/99 |
COMS W4733 COMPUTATIONAL ASPECTS OF ROBOTICS. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136COMS W3137) Introduction to fundamental problems and algorithms in robotics. Topics include configuration spaces, motion and sensor models, search and sampling-based planning, state estimation, localization and mapping, perception, and learning
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4733 | 001/14014 | F 1:10pm - 3:40pm 501 Northwest Corner | Tony Dear | 3.00 | 95/164 |
COMS 4733 | V01/18546 | | Tony Dear | 3.00 | 5/99 |
COMS W4735 VISUAL INTERFACES TO COMPUTERS. 3.00 points .
Prerequisites: ( COMS W3134 or COMS W3136 or COMS W3137 ) Visual input as data and for control of computer systems. Survey and analysis of architecture, algorithms, and underlying assumptions of commercial and research systems that recognize and interpret human gestures, analyze imagery such as fingerprint or iris patterns, generate natural language descriptions of medical or map imagery. Explores foundations in human psychophysics, cognitive science, and artificial intelligence
COMS W4737 Biometrics. 3 points .
Prerequisites: a background at the sophomore level in computer science, engineering, or like discipline.
In this course. we will explore the latest advances in biometrics as well as the machine learning techniques behind them. Students will learn how these technologies work and how they are sometimes defeated. Grading will be based on homework assignments and a final project. There will be no midterm or final exam. This course shares lectures with COMS E6737 . Students taking COMS E6737 are required to complete additional homework problems and undertake a more rigorous final project. Students will only be allowed to earn credit for COMS W4737 or COMS E6737 and not both.
COMS W4762 Machine Learning for Functional Genomics. 3 points .
Prerequisites: Proficiency in a high-level programming language (Python/R/Julia). An introductory machine learning class (such as COMS 4771 Machine Learning) will be helpful but is not required.
Prerequisites: see notes re: points
This course will introduce modern probabilistic machine learning methods using applications in data analysis tasks from functional genomics, where massively-parallel sequencing is used to measure the state of cells: e.g. what genes are being expressed, what regions of DNA (“chromatin”) are active (“open”) or bound by specific proteins.
COMS E4762 Machine Learning for Functional Genomics. 3.00 points .
This course will introduce modern probabilistic machine learning methods using applications in data analysis tasks from functional genomics, where massively-parallel sequencing is used to measure the state of cells: e.g. what genes are being expressed, what regions of DNA (“chromatin”) are active (“open”) or bound by specific proteins
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4762 | 001/11956 | F 1:10pm - 3:40pm Room TBA | David Knowles | 3.00 | 8/100 |
COMS W4771 MACHINE LEARNING. 3.00 points .
Prerequisites: Any introductory course in linear algebra and any introductory course in statistics are both required. Highly recommended: COMS W4701 or knowledge of Artificial Intelligence. Topics from generative and discriminative machine learning including least squares methods, support vector machines, kernel methods, neural networks, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models and hidden Markov models. Algorithms implemented in MATLAB
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4771 | 001/12092 | T Th 1:10pm - 2:25pm 451 Computer Science Bldg | Nakul Verma | 3.00 | 73/110 |
COMS 4771 | 002/12093 | T Th 2:40pm - 3:55pm 451 Computer Science Bldg | Nakul Verma | 3.00 | 78/110 |
COMS 4771 | V01/16720 | | Nakul Verma | 3.00 | 5/99 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4771 | 001/11957 | T Th 2:40pm - 3:55pm Room TBA | Nakul Verma | 3.00 | 0/110 |
COMS 4771 | V01/17526 | | Nakul Verma | 3.00 | 0/99 |
COMS W4772 ADVANCED MACHINE LEARNING. 3.00 points .
Prerequisites: ( COMS W4771 ) or instructor's permission; knowledge of linear algebra & introductory probability or statistics is required. An exploration of advanced machine learning tools for perception and behavior learning. How can machines perceive, learn from, and classify human activity computationally? Topics include appearance-based models, principal and independent components analysis, dimensionality reduction, kernel methods, manifold learning, latent models, regression, classification, Bayesian methods, maximum entropy methods, real-time tracking, extended Kalman filters, time series prediction, hidden Markov models, factorial HMMS, input-output HMMs, Markov random fields, variational methods, dynamic Bayesian networks, and Gaussian/Dirichlet processes. Links to cognitive science
COMS W4773 Machine Learning Theory. 3 points .
Prerequisites: Machine Learning (COMS W4771). Background in probability and statistics, linear algebra, and multivariate calculus. Ability to program in a high-level language, and familiarity with basic algorithm design and coding principles.
Core topics from unsupervised learning such as clustering, dimensionality reduction and density estimation will be studied in detail. Topics in clustering: k-means clustering, hierarchical clustering, spectral clustering, clustering with various forms of feedback, good initialization techniques and convergence analysis of various clustering procedures. Topics in dimensionality reduction: linear techniques such as PCA, ICA, Factor Analysis, Random Projections, non-linear techniques such as LLE, IsoMap, Laplacian Eigenmaps, tSNE, and study of embeddings of general metric spaces, what sorts of theoretical guarantees can one provide about such techniques. Miscellaneous topics: design and analysis of data structures for fast Nearest Neighbor search such as Cover Trees and LSH. Algorithms will be implemented in either Matlab or Python.
COMS E4773 Machine Learning Theory. 3.00 points .
Theoretical study of algorithms for machine learning and high-dimensional data analysis. Topics include high-dimensional probability, theory of generalization and statistical learning, online learning and optimization, spectral analysis
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4773 | 001/12094 | T Th 8:40am - 9:55am 451 Computer Science Bldg | Daniel Hsu | 3.00 | 34/60 |
COMS W4774 Unsupervised Learning. 3.00 points .
Prerequisites: Solid background in multivariate calculus, linear algebra, basic probability, and algorithms.
Prerequisites: see notes re: points Core topics from unsupervised learning such as clustering, dimensionality reduction and density estimation will be studied in detail. Topics in clustering: k-means clustering, hierarchical clustering, spectral clustering, clustering with various forms of feedback, good initialization techniques and convergence analysis of various clustering procedures. Topics in dimensionality reduction: linear techniques such as PCA, ICA, Factor Analysis, Random Projections, non-linear techniques such as LLE, IsoMap, Laplacian Eigenmaps, tSNE, and study of embeddings of general metric spaces, what sorts of theoretical guarantees can one provide about such techniques. Miscellaneous topics: design and analysis of datastructures for fast Nearest Neighbor search such as Cover Trees and LSH. Algorithms will be implemented in either Matlab or Python
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4774 | 001/11958 | T Th 1:10pm - 2:25pm Room TBA | Nakul Verma | 3.00 | 0/50 |
COMS W4775 Causal Inference. 3.00 points .
Prerequisites: Discrete Math, Calculus, Statistics (basic probability, modeling, experimental design), some programming experience.
Prerequisites: see notes re: points Causal Inference theory and applications. The theoretical topics include the 3-layer causal hierarchy, causal bayesian networks, structural learning, the identification problem and the do-calculus, linear identifiability, bounding, and counterfactual analysis. The applied part includes intersection with statistics, the empirical-data sciences (social and health), and AI and ML
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4775 | 001/11959 | M W 4:10pm - 5:25pm Room TBA | Elias Bareinboim | 3.00 | 0/50 |
COMS E4775 Causal Inference. 3 points .
Prerequisites: (COMS4711W) and Discrete Math, Calculus, Statistics (basic probability, modeling, experimental design), Some programming experience
Causal Inference theory and applications. The theoretical topics include the 3-layer causal hierarchy, causal bayesian networks, structural learning, the identification problem and the do-calculus, linear identifiability, bounding, and counterfactual analysis. The applied part includes intersection with statistics, the empirical-data sciences (social and health), and AI and ML.
COMS W4776 Machine Learning for Data Science. 3 points .
Prerequisites: ( STAT GU4001 or IEOR E4150 ) and linear algebra.
Introduction to machine learning, emphasis on data science. Topics include least square methods, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models, hidden Markov models, support vector machines kernel methods. Emphasizes methods and problems relevant to big data. Students may not receive credit for both COMS W4771 and W4776.
COMS W4824 COMPUTER ARCHITECTURE. 3.00 points .
COMS W4835 COMPUTER ORGANIZATION II. 3.00 points .
COMS E4899 Research Training. 0.00 points .
COMS W4901 Projects in Computer Science. 1-3 points .
Prerequisites: Approval by a faculty member who agrees to supervise the work.
A second-level independent project involving laboratory work, computer programming, analytical investigation, or engineering design. May be repeated for credit, but not for a total of more than 3 points of degree credit. Consult the department for section assignment.
COMS W4910 CURRICULAR PRACTICAL TRAINING. 1.00 point .
COMS E4995 COMPUTER ARTS/VIDEO GAMES. 3.00 points .
Special topics arranged as the need and availability arises. Topics are usually offered on a one-time basis. Since the content of this course changes each time it is offered, it may be repeated for credit. Consult the department for section assignment
COMS W4995 TOPICS IN COMPUTER SCIENCE. 3.00 points .
Prerequisites: Instructor's permission. Selected topics in computer science. Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
COMS 4995 | 001/12095 | T Th 8:40am - 9:55am 1024 Seeley W. Mudd Building | Andrew Blumberg | 3.00 | 26/40 |
COMS 4995 | 002/12096 | M W 5:40pm - 6:55pm 1024 Seeley W. Mudd Building | Yongwhan Lim | 3.00 | 11/50 |
COMS 4995 | 003/12098 | Th 4:10pm - 6:40pm 1127 Seeley W. Mudd Building | Christian Swinehart | 3.00 | 33/40 |
COMS 4995 | 004/12099 | T Th 5:40pm - 6:55pm 451 Computer Science Bldg | Austin Reiter | 3.00 | 95/110 |
COMS 4995 | 005/12101 | F 10:10am - 12:40pm 1127 Seeley W. Mudd Building | Michelle Levine | 3.00 | 24/40 |
COMS 4995 | 006/12102 | T 1:10pm - 3:40pm 1127 Seeley W. Mudd Building | Gary Zamchick | 3.00 | 39/40 |
COMS 4995 | 008/12104 | W 4:10pm - 6:40pm 451 Computer Science Bldg | Jae Lee, Hans Montero | 3.00 | 74/110 |
COMS 4995 | 030/12956 | T 7:00pm - 9:30pm 413 Kent Hall | Adam Kelleher | 3.00 | 63/70 |
COMS 4995 | 032/12965 | W 4:10pm - 6:40pm 329 Pupin Laboratories | Vijay Pappu | 3.00 | 101/100 |
COMS 4995 | V01/18718 | | Andrew Blumberg | 3.00 | 0/99 |
COMS 4995 | V02/15425 | | Yongwhan Lim | 3.00 | 0/99 |
COMS 4995 | V08/16721 | | Jae Lee, Hans Montero | 3.00 | 2/99 |
COMS 4995 | V32/20861 | | Vijay Pappu | 3.00 | 20/99 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
COMS 4995 | 001/11960 | T 4:10pm - 6:40pm Room TBA | Paul Blaer, Jason Cahill | 3.00 | 0/40 |
COMS 4995 | 002/11961 | F 10:10am - 12:40pm Room TBA | Bjarne Stroustrup | 3.00 | 13/33 |
COMS 4995 | 003/11962 | M W 1:10pm - 2:25pm Room TBA | Stephen Edwards | 3.00 | 30/70 |
COMS 4995 | 004/11963 | W 4:10pm - 6:40pm Room TBA | Jae Lee, Hans Montero | 3.00 | 0/110 |
COMS 4995 | 005/11964 | T Th 2:40pm - 3:55pm Room TBA | Peter Belhumeur | 3.00 | 62/125 |
COMS 4995 | 006/11965 | T Th 5:40pm - 6:55pm Room TBA | Itsik Pe'er | 3.00 | 3/40 |
COMS 4995 | 007/11966 | T Th 5:40pm - 6:55pm Room TBA | Yongwhan Lim | 3.00 | 1/100 |
COMS 4995 | 008/11967 | T 1:10pm - 3:40pm Room TBA | Gary Zamchick | 3.00 | 44/40 |
COMS 4995 | 009/11968 | W 10:10am - 12:40pm Room TBA | Michelle Levine | 3.00 | 5/40 |
COMS 4995 | 010/11969 | Th 4:10pm - 6:40pm Room TBA | Homayoon Beigi | 3.00 | 15/60 |
COMS 4995 | 011/13628 | T Th 4:10pm - 5:25pm Room TBA | Hugh Thomas | 3.00 | 0/100 |
COMS 4995 | 012/15929 | W 7:00pm - 9:30pm Room TBA | Yihao Zhang | 3.00 | 2/50 |
COMS 4995 | 030/13530 | M 7:00pm - 9:30pm Room TBA | Andi Cupallari | 3.00 | 14/120 |
COMS 4995 | 031/13532 | W 7:00pm - 9:30pm Room TBA | Andrei Simion | 3.00 | 21/170 |
COMS 4995 | 032/13534 | T 4:10pm - 6:40pm Room TBA | Vijay Pappu | 3.00 | 12/120 |
COMS 4995 | 033/13533 | Th 7:00pm - 9:30pm Room TBA | Vijay Pappu | 3.00 | 9/135 |
COMS 4995 | V03/17527 | | Stephen Edwards | 3.00 | 0/99 |
COMS 4995 | V10/17528 | | Homayoon Beigi | 3.00 | 0/99 |
COMS 4995 | V32/17555 | | Vijay Pappu | 3.00 | 0/99 |
COMS W4996 Special topics in computer science, II. 3 points .
Prerequisites: Instructor's permission.
A continuation of COMS W4995 when the special topic extends over two terms.
CSEE W3826 FUNDAMENTALS OF COMPUTER ORG. 3.00 points .
CSEE W3827 FUNDAMENTALS OF COMPUTER SYSTS. 3.00 points .
Prerequisites: an introductory programming course. Fundamentals of computer organization and digital logic. Boolean algebra, Karnaugh maps, basic gates and components, flipflops and latches, counters and state machines, basics of combinational and sequential digital design. Assembly language, instruction sets, ALU’s, single-cycle and multi-cycle processor design, introduction to pipelined processors, caches, and virtual memory
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
CSEE 3827 | 001/12121 | T Th 10:10am - 11:25am 207 Mathematics Building | Daniel Rubenstein | 3.00 | 134/152 |
CSEE 3827 | 002/12122 | T Th 11:40am - 12:55pm 428 Pupin Laboratories | Daniel Rubenstein | 3.00 | 136/147 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
CSEE 3827 | 001/11985 | T Th 11:40am - 12:55pm Room TBA | Martha Kim, Martha Barker | 3.00 | 164/164 |
CSEE 3827 | 002/11986 | T Th 1:10pm - 2:25pm Room TBA | Martha Kim, Martha Barker | 3.00 | 153/164 |
CSEE W4119 COMPUTER NETWORKS. 3.00 points .
Introduction to computer networks and the technical foundations of the Internet, including applications, protocols, local area networks, algorithms for routing and congestion control, security, elementary performance evaluation. Several written and programming assignments required
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
CSEE 4119 | 002/12160 | T Th 11:40am - 12:55pm 451 Computer Science Bldg | Xia Zhou | 3.00 | 101/110 |
CSEE 4119 | V02/15427 | | Xia Zhou | 3.00 | 6/99 |
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
CSEE 4119 | 001/14071 | T Th 4:10pm - 5:25pm Room TBA | Ethan Katz-Bassett, Thomas Koch | 3.00 | 47/120 |
CSEE 4119 | 002/14070 | T Th 5:40pm - 6:55pm Room TBA | Ethan Katz-Bassett, Thomas Koch | 3.00 | 25/120 |
CSEE W4121 COMPUTER SYSTEMS FOR DATA SCIENCE. 3.00 points .
Prerequisites: Background in Computer System Organization and good working knowledge of C/C++. Corequisites: CSOR W4246 Algorithms for Data Science, STAT W4203 Probability Theory, or equivalent as approved by faculty advisor. An introduction to computer architecture and distributed systems with an emphasis on warehouse scale computing systems. Topics will include fundamental tradeoffs in computer systems, hardware and software techniques for exploiting instruction-level parallelism, data-level parallelism and task level parallelism, scheduling, caching, prefetching, network and memory architecture, latency and throughput optimizations, specialization, and an introduction to programming data center computers
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
CSEE 4121 | 002/12974 | Th 7:00pm - 9:30pm 417 International Affairs Bldg | Sambit Sahu, Robert Kramer | 3.00 | 178/175 |
CSEE W4140 NETWORKING LABORATORY. 3.00 points .
Prerequisites: ( CSEE W4119 ) or equivalent. In this course, students will learn how to put principles into practice, in a hands-on-networking lab course. The course will cover the technologies and protocols of the Internet using equipment currently available to large internet service providers such as CISCO routers and end systems. A set of laboratory experiments will provide hands-on experience with engineering wide-area networks and will familiarize students with the Internet Protocol (IP), Address Resolution Protocol (ARP), Internet Control Message Protocol (ICMP), User Datagram Protocol (UDP) and Transmission Control Protocol (TCP), the Domain Name System (DNS), routing protocols (RIP, OSPF, BGP), network management protocols (SNMP, and application-level protocols (FTP, TELNET, SMTP)
CSEE W4823 Advanced Logic Design. 3 points .
Prerequisites: ( CSEE W3827 ) or a half semester introduction to digital logic, or the equivalent.
An introduction to modern digital system design. Advanced topics in digital logic: controller synthesis (Mealy and Moore machines); adders and multipliers; structured logic blocks (PLDs, PALs, ROMs); iterative circuits. Modern design methodology: register transfer level modelling (RTL); algorithmic state machines (ASMs); introduction to hardware description languages (VHDL or Verilog); system-level modelling and simulation; design examples.
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
CSEE 4823 | 001/11307 | T Th 2:40pm - 3:55pm Room TBA | Mingoo Seok | 3 | 24/80 |
CSEE W4824 COMPUTER ARCHITECTURE. 3.00 points .
Prerequisites: ( CSEE W3827 ) or equivalent. Focuses on advanced topics in computer architecture, illustrated by case studies from classic and modern processors. Fundamentals of quantitative analysis. Pipelining. Memory hierarchy design. Instruction-level and thread-level parallelism. Data-level parallelism and graphics processing units. Multiprocessors. Cache coherence. Interconnection networks. Multi-core processors and systems-on-chip. Platform architectures for embedded, mobile, and cloud computing
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
CSEE 4824 | 001/11987 | M W 10:10am - 11:25am Room TBA | Simha Sethumadhavan | 3.00 | 31/55 |
CSEE W4840 EMBEDDED SYSTEMS. 3.00 points .
Prerequisites: ( CSEE W4823 ) Embedded system design and implementation combining hardware and software. I/O, interfacing, and peripherals. Weekly laboratory sessions and term project on design of a microprocessor-based embedded system including at least one custom peripheral. Knowledge of C programming and digital logic required
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
CSEE 4840 | 001/12033 | M W 1:10pm - 2:25pm 451 Computer Science Bldg | Stephen Edwards | 3.00 | 97/110 |
CSEE W4868 SYSTEM-ON-CHIP PLATFORMS. 3.00 points .
Prerequisites: ( COMS W3157 ) and ( CSEE W3827 ) Design and programming of System-on-Chip (SoC) platforms. Topics include: overview of technology and economic trends, methodologies and supporting CAD tools for system-level design, models of computation, the SystemC language, transaction-level modeling, software simulation and virtual platforms, hardware-software partitioning, high-level synthesis, system programming and device drivers, on-chip communication, memory organization, power management and optimization, integration of programmable processor cores and specialized accelerators. Case studies of modern SoC platforms for various classes of applications
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
CSEE 4868 | 001/11988 | T Th 11:40am - 12:55pm Room TBA | Luca Carloni | 3.00 | 16/60 |
CBMF W4761 COMPUTATIONAL GENOMICS. 3.00 points .
Prerequisites: Working knowledge of at least one programming language, and some background in probability and statistics. Computational techniques for analyzing genomic data including DNA, RNA, protein and gene expression data. Basic concepts in molecular biology relevant to these analyses. Emphasis on techniques from artificial intelligence and machine learning. String-matching algorithms, dynamic programming, hidden Markov models, expectation-maximization, neural networks, clustering algorithms, support vector machines. Students with life sciences backgrounds who satisfy the prerequisites are encouraged to enroll
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
CBMF 4761 | 001/12050 | M W 5:40pm - 6:55pm 1127 Seeley W. Mudd Building | Itsik Pe'er | 3.00 | 32/60 |
CBMF 4761 | V01/15241 | | Itsik Pe'er | 3.00 | 1/99 |
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PhD students in the Department of Computer Science may focus their research in the following areas:
For specific program requirements, please refer to the departmental program website
The UBC Department of Computer Science has many contacts in the computing industry. A strong rapport between the industry and research communities is beneficial to both, especially in cases where the department focuses its research to developing real-world applications.
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Program enquiries, admission information & requirements, 1) check eligibility, minimum academic requirements.
The Faculty of Graduate and Postdoctoral Studies establishes the minimum admission requirements common to all applicants, usually a minimum overall average in the B+ range (76% at UBC). The graduate program that you are applying to may have additional requirements. Please review the specific requirements for applicants with credentials from institutions in:
Each program may set higher academic minimum requirements. Please review the program website carefully to understand the program requirements. Meeting the minimum requirements does not guarantee admission as it is a competitive process.
Applicants from a university outside Canada in which English is not the primary language of instruction must provide results of an English language proficiency examination as part of their application. Tests must have been taken within the last 24 months at the time of submission of your application.
Minimum requirements for the two most common English language proficiency tests to apply to this program are listed below:
Overall score requirement : 100
Overall score requirement : 7.0
Some programs require additional test scores such as the Graduate Record Examination (GRE) or the Graduate Management Test (GMAT). The requirements for this program are:
The GRE is not required.
September 2024 intake, application open date, canadian applicants, international applicants, deadline explanations.
Deadline to submit online application. No changes can be made to the application after submission.
Deadline to upload scans of official transcripts through the applicant portal in support of a submitted application. Information for accessing the applicant portal will be provided after submitting an online application for admission.
Deadline for the referees identified in the application for admission to submit references. See Letters of Reference for more information.
Transcripts.
All applicants have to submit transcripts from all past post-secondary study. Document submission requirements depend on whether your institution of study is within Canada or outside of Canada.
A minimum of three references are required for application to graduate programs at UBC. References should be requested from individuals who are prepared to provide a report on your academic ability and qualifications.
Many programs require a statement of interest , sometimes called a "statement of intent", "description of research interests" or something similar.
Students in research-based programs usually require a faculty member to function as their thesis supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.
Citizenship verification.
Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.
All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.
Fees | Canadian Citizen / Permanent Resident / Refugee / Diplomat | International |
---|---|---|
$114.00 | $168.25 | |
Tuition * | ||
Installments per year | 3 | 3 |
Tuition | $1,838.57 | $3,230.06 |
Tuition (plus annual increase, usually 2%-5%) | $5,515.71 | $9,690.18 |
Int. Tuition Award (ITA) per year ( ) | $3,200.00 (-) | |
Other Fees and Costs | ||
(yearly) | $1,116.60 (approx.) | |
Estimate your with our interactive tool in order to start developing a financial plan for your graduate studies. |
Applicants to UBC have access to a variety of funding options, including merit-based (i.e. based on your academic performance) and need-based (i.e. based on your financial situation) opportunities.
All full-time PhD students will be provided with a funding package of at least $31,920 for each of the first four years of their PhD program. The funding package consists of any combination of internal or external awards, teaching-related work, research assistantships, and graduate academic assistantships. This support is contingent on full-time registration as a UBC Graduate student, satisfactory performance in assigned teaching and research assistantship duties, and good standing with satisfactory progress in your academic performance. CS students are expected to apply for fellowships or scholarship to which they are eligible.
All applicants are encouraged to review the awards listing to identify potential opportunities to fund their graduate education. The database lists merit-based scholarships and awards and allows for filtering by various criteria, such as domestic vs. international or degree level.
Many professors are able to provide Research Assistantships (GRA) from their research grants to support full-time graduate students studying under their supervision. The duties constitute part of the student's graduate degree requirements. A Graduate Research Assistantship is considered a form of fellowship for a period of graduate study and is therefore not covered by a collective agreement. Stipends vary widely, and are dependent on the field of study and the type of research grant from which the assistantship is being funded.
Graduate programs may have Teaching Assistantships available for registered full-time graduate students. Full teaching assistantships involve 12 hours work per week in preparation, lecturing, or laboratory instruction although many graduate programs offer partial TA appointments at less than 12 hours per week. Teaching assistantship rates are set by collective bargaining between the University and the Teaching Assistants' Union .
Academic Assistantships are employment opportunities to perform work that is relevant to the university or to an individual faculty member, but not to support the student’s graduate research and thesis. Wages are considered regular earnings and when paid monthly, include vacation pay.
Canadian and US applicants may qualify for governmental loans to finance their studies. Please review eligibility and types of loans .
All students may be able to access private sector or bank loans.
Many foreign governments provide support to their citizens in pursuing education abroad. International applicants should check the various governmental resources in their home country, such as the Department of Education, for available scholarships.
The possibility to pursue work to supplement income may depend on the demands the program has on students. It should be carefully weighed if work leads to prolonged program durations or whether work placements can be meaningfully embedded into a program.
International students enrolled as full-time students with a valid study permit can work on campus for unlimited hours and work off-campus for no more than 20 hours a week.
A good starting point to explore student jobs is the UBC Work Learn program or a Co-Op placement .
Students with taxable income in Canada may be able to claim federal or provincial tax credits.
Canadian residents with RRSP accounts may be able to use the Lifelong Learning Plan (LLP) which allows students to withdraw amounts from their registered retirement savings plan (RRSPs) to finance full-time training or education for themselves or their partner.
Please review Filing taxes in Canada on the student services website for more information.
Applicants have access to the cost estimator to develop a financial plan that takes into account various income sources and expenses.
111 students graduated between 2005 and 2013. Of these, career information was obtained for 106 alumni (based on research conducted between Feb-May 2016):
Sample employers outside higher education, sample job titles outside higher education, phd career outcome survey, career options.
Our faculty and students actively interact with industry in numerous fields. Via internships, consulting and the launching of new companies, they contribute to the state-of-the-art in environmental monitoring, energy prediction, software, cloud computing, search engines, social networks, advertising, e-commerce, electronic trading, entertainment games, special effects in movies, robotics, bioinformatics, biomedical engineering, and more.
Job Title Senior Director, Product & Business Development
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These statistics show data for the Doctor of Philosophy in Computer Science (PhD). Data are separated for each degree program combination. You may view data for other degree options in the respective program profile.
2023 | 2022 | 2021 | 2020 | 2019 | |
---|---|---|---|---|---|
Applications | 281 | 265 | 375 | 299 | 278 |
Offers | 31 | 40 | 41 | 45 | 26 |
New Registrations | 14 | 15 | 20 | 20 | 16 |
Total Enrolment | 129 | 124 | 116 | 98 | 81 |
Upcoming doctoral exams, tuesday, 23 july 2024 - 2:00pm - x836, icics building, 2366 main mall, tuesday, 30 july 2024 - 10:00am - x836, icics building, 2366 main mall.
These videos contain some general advice from faculty across UBC on finding and reaching out to a supervisor. They are not program specific.
This list shows faculty members with full supervisory privileges who are affiliated with this program. It is not a comprehensive list of all potential supervisors as faculty from other programs or faculty members without full supervisory privileges can request approvals to supervise graduate students in this program.
Year | Citation |
---|---|
2024 | Using artificial intelligence methods, Dr. Dirks developed machine learning models to unlock the information contained in spectral data. Demonstrated applications include grade estimation in mining and food quality assessment in agriculture. |
2024 | Dr. Su studied 3D computer vision for human digitalization, which converts real-world images and videos into 3D animatable avatars. His methods simplify complicated motion capture pipelines, showing a promising way for 3D avatar creations from everyday devices. |
2024 | Dr. Vining studied how computers operate on geometry and shapes, and how geometric problems can be solved with discrete optimization algorithms. By combining numerical optimization techniques with combinatorial search frameworks, he devised new algorithms that solve challenging problems in simulation, computer graphics, and video games. |
2024 | Dr. Ritschel studied the design of programming tools for end-users without previous coding experience. He investigated block-based programming languages and enriched them with visual features that help end-users write larger, more complex programs. His findings can guide the future development of more expressive end-user friendly programming tools. |
2024 | Dr. Jawahar explored how deep learning models in natural language processing could be more efficient. He introduced new, cutting-edge methods using neural architecture search, improving efficiency and performance tradeoffs in tasks like autocomplete, machine translation, and language modeling. |
2024 | Dr. Xing explored and improved the detection of topic shifts in natural language and multimedia using data-driven approaches. He proposed enhanced topic segmentation models with better coherence analysis strategies, showing potential to benefit other natural language understanding tasks like text summarization and dialogue modeling. |
2024 | Dr. Cang examined emotionally expressive touch behaviour for human-robot interaction. To be truly reactive, devices must address the dynamic nature of emotion. For her dissertation, she developed multi-stage machine learning protocols to train robots to respond to your evolving feelings. |
2024 | Dr. Newman designed tools for running and analyzing complex, electronic auctions, with applications to markets for agricultural trade in developing countries and the sale of wireless spectrum rights. His work provides a blueprint for how economists can use computer simulations to compare auction designs. |
2024 | Dr. Suhail has made significant strides in computer vision by pioneering diverse methodologies that elevate semantic comprehension and geometric reasoning abilities within computer vision systems. His works have received nominations for Best Paper Awards, highlighting the substantial impact of his work in the field. |
2024 | Dr. Banados Schwerter studied the formal requirements for detecting type inconsistencies in programming languages that combine static and dynamic type checking, and a novel reporting technique for these errors. His research will assist the design of new programming languages and help their future programmers to find and fix programming mistakes. |
Same specialization.
Further information, specialization.
Computer Science covers Bayesian statistics and applications, bioinformatics, computational intelligence (computational vision, automated reasoning, multi-agent systems, intelligent interfaces, and machine learning), computer communications, databases, distributed and parallel systems, empirical analysis of algorithms, computer graphics, human-computer interaction, hybrid systems, integrated systems design, networks, network security, networking and multimedia, numerical methods and geometry in computer graphics, operating systems, programming languages, robotics, scientific computation, software engineering, visualization, and theoretical aspects of computer science (computational complexity, computational geometry, analysis of complex graphs, and parallel processing).
Program website, faculty overview, academic unit, program identifier, classification, social media channels, supervisor search.
Departments/Programs may update graduate degree program details through the Faculty & Staff portal. To update contact details for application inquiries, please use this form .
My experience as a non-degree student was really positive. I loved the way lectures, tutorials, labs, assignments and projects all complemented each other. I found the lectures stimulating and the professors and TAs encouraging. I also loved just being on the UBC campus. I'm surrounded by nature (...
I applied to UBC in 2020, during the pandemic. It was a close call between working with Marcus Brubaker, who co-founded my former employer Structura Biotechnology, before becoming an Assistant Professor at York University, and working with Khanh Dao Duc at UBC. Khanh introduced me to his...
I think three factors had a differentiating effect on this decision: UBC's unique multidisciplinary environment which is key to my research as a computer scientist and bioinformatician. UBC being on the West Coast generally and Vancouver specifically and the amazing weather and nature that comes...
Our community of scholars is one of the world’s finest, committed to discovering and sharing knowledge, and to tackling the challenges that face our world.
Vikram S. Pandit Professor of Computer Science, Columbia University. Room 723, mcollins [at] cs.columbia.[first 3 letters in "education"]
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PhD in Computer Science at the prestigious Columbia University is a prestigious degree that offers in-depth learning in Computer Science. Being a renowned university, Columbia University receives enough funds to ensure the best education facilities for its students across all programs. This doctorate program offered full-time primarily focuses on the practical implementation of fresh ideas through rigorous study and research. The students are encouraged to add new aspects and findings to the existing area of knowledge. PhD in Computer Science at CU is ranked globally by estimated organisations. Such recognition speaks volumes about the course’s importance and effectiveness in the present scenario. The top-notch faculty, modern facilities, and the aura of creativity and innovation in the CU campus is a life-changing experience for the students looking forward to kickstarting or upgrading their careers. Overall, a PhD in Computer Science at Columbia University is an excellent opportunity to grow into a learned professional and bring new developments in the world.
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For full details on the PhD programs, see the PhD Program .
The UBC Department of Computer Science PhD program has four main components:
Completing the research program.
The objective of the comprehensive course requirement is to ensure that the student obtains an equal load of courses. That is, all courses are treated equally and all areas are treated equally
To fulfill this requirement, the student must complete six (6) courses:
Please refer to Comprehensive Course Requirement for details.
The objective of the Research Proficiency Evaluation is to ensure a student shows sufficient promise in research skills necessary to successfully carry out a PhD in our environment. The student will work with one or more supervisors on a jointly determined research project, which can form the basis of a potential thesis topic. The student will then present the work, both in writing and orally, to a committee of faculty early in their time in the PhD program.
Students benefit from the RPE by making an early engagement with their supervisory committee and by receiving early feedback from a committee of experts on their potential success in the PhD program, thus minimizing the chance of facing difficulties after years of investment.
Please refer to RPE for details.
After completing the comprehensive course requirements, the student will move on to researching and writing a PhD thesis proposal under the direction of their supervisor(s).
After completing the thesis proposal, the student will take an oral thesis proposal examination administered by the PhD thesis committee. The chair of this examination will be a faculty member not on the thesis committee, and will be chosen by the student's thesis supervisor. The sole purpose of this exam is the defense of the student's thesis proposal, which must be presented in written form to the thesis committee at least two weeks prior to the examination. The examination must take place within 24 months of the time that the student enters the PhD program.
Please refer to PhD Thesis Proposal for details.
Once the student has passed the thesis proposal exam, the student must carry out the research program in accordance with the research proposal under the supervisor's guidance. The PhD thesis describing the research findings must be written by the student and approved by the PhD supervisory committee. In order to obtain the PhD degree, the thesis must also be approved by an external examiner outside UBC and two UBC examiners (one from this department and the other from another department within UBC) and defended at the final oral examination set up by the Faculty of Graduate Studies.
School - June 26, 2024
Change is accelerating. Generative AI is redefining the shape and speed of innovation. Columbia’s Master of Science in Technology Management program prepares technology professionals to future-proof their practice.
Columbia University pioneered the Ivy League’s first Technology Management master’s program 20 years ago to empower professionals to make an economic and social impact in a world of constant change and disruption. We have institutionalized technology’s continuous improvement and deployment philosophy in our curriculum.
As technology continues to redefine operations, a paradigm shift has occurred. Previously, strategy and policy preceded execution. Today, execution leads, followed by strategy, with policy lagging behind. This evolution underscores technology’s pivotal role as a catalyst for innovation, growth, and risk, and the Technology Management program curriculum has been revised to keep up with industry innovations.
“Tech leadership demands constant learning and adaptation,” said Dr. Alexis Wichowski, Technology Management’s program director and a professor of practice. “Our newly revised M.S. in Technology Management program now reflects that reality. This program is not just for tech people or business people: It trains future leaders to be equally fluent in both.”
The program prepares students to thrive in these conditions with solid fundamentals in core technology and business principles and also offers continually updated courses that reflect current trends. The revised curriculum is the first of its kind to include an explicit focus on ethical leadership, reflecting the ways in which today’s technology leaders must negotiate not only business and technology decisions but also the application of concepts like “do no harm” in relation to the deployment of new technologies.
With options to study either in person or online with four immersive residencies, the program offers unparalleled insider access to one of the world’s most dynamic and innovative technology capitals. The faculty and program team, composed of industry-leading practitioners including 12x serial entrepreneur Art Chang , global business leader and cybersecurity expert Cristina Dolan , and leading technology and media corporate strategist Stephano Kim , brings real-world experience and expertise to the classroom, equipping our students with the tools they need to succeed and the networks they need to achieve their career goals.
The program doesn’t just teach theory—it also provides hands-on experiential learning through projects, internships, and networking opportunities. The curriculum constantly evolves to keep pace with the latest developments in technology and business, ensuring that students graduate with the skills and knowledge they need to excel in their careers. With a community of more than 1,000 alumni who have gone on to lead and innovate at companies like Google, Apple, NASA, and more, students will be equipped to adapt and keep pace in an ever-changing technology landscape as they join a global network of peers shaping the future.
About the Program
Columbia University's Master of Science in Technology Management is designed to respond to the urgent need for strategic perspectives, critical thinking, and exceptional communication skills at all levels of the workplace and across all types of organizations.
Related news, summer special events in new york city learn about what’s happening on campus this summer. in the community, school new york city high school students complete their columbia stem program with a series of events at morgan stanley over twenty nyc high school students in columbia’s youth in stem program spent a week at the financial company. school honoring the achievements of the sps community at the sps excellence awards learn about the winners of this year's sps excellence awards. all news footer social links.
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Upcoming events, in the news, press mentions, dean boyce's statement on amicus brief filed by president bollinger.
President Bollinger announced that Columbia University along with many other academic institutions (sixteen, including all Ivy League universities) filed an amicus brief in the U.S. District Court for the Eastern District of New York challenging the Executive Order regarding immigrants from seven designated countries and refugees. Among other things, the brief asserts that “safety and security concerns can be addressed in a manner that is consistent with the values America has always stood for, including the free flow of ideas and people across borders and the welcoming of immigrants to our universities.”
This recent action provides a moment for us to collectively reflect on our community within Columbia Engineering and the importance of our commitment to maintaining an open and welcoming community for all students, faculty, researchers and administrative staff. As a School of Engineering and Applied Science, we are fortunate to attract students and faculty from diverse backgrounds, from across the country, and from around the world. It is a great benefit to be able to gather engineers and scientists of so many different perspectives and talents – all with a commitment to learning, a focus on pushing the frontiers of knowledge and discovery, and with a passion for translating our work to impact humanity.
I am proud of our community, and wish to take this opportunity to reinforce our collective commitment to maintaining an open and collegial environment. We are fortunate to have the privilege to learn from one another, and to study, work, and live together in such a dynamic and vibrant place as Columbia.
Mary C. Boyce Dean of Engineering Morris A. and Alma Schapiro Professor
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Computer Science Department 500 West 120 Street, Room 450 MC0401 New York, New York 10027 Main Office: +1-212-853-8400 Directions Map Directory
PhD Program; MS Bridge Program; Computer Engineering Program; ... Computer Science Department 500 West 120 Street, Room 450 MC0401 New York, New York 10027 ... President Bollinger announced that Columbia University along with many other academic institutions (sixteen, ...
Almost all doctoral research advisors are tenured or tenure-track faculty members in the Computer Science Department. But in rare cases a PhD student's research may be advised by a research scientist or an affiliated faculty member from another ... Computer Science at Columbia University. Upcoming Events View All >> In the News. Press Mentions.
Computer Science Department 500 West 120 Street, Room 450 MC0401 New York, New York 10027 Main Office: +1-212-853-8400 Directions Map Directory
The Master of Science (MS) program is intended for those who wish to broaden and deepen their understanding of computer science. Columbia University and the New York City environment provide excellent career opportunities in multiple industries. The program provides a unique opportunity to develop leading-edge in-depth knowledge of specific ...
Students should discuss this specialization option with their Ph.D. advisor and their department's director for graduate studies. The specialization consists of either five (5) courses from the lists below, or four (4) courses plus one (1) additional course approved by the curriculum committee. All courses must be taken for a letter grade and ...
Computer Science Department 500 West 120 Street, Room 450 MC0401 New York, New York 10027 Main Office: +1-212-853-8400 Directions Map Directory
Those pursuing PhD studies will work alongside world-class researchers to innovate new techniques and algorithms as they tackle hard problems across science, technology, and society. ... Department of Computer Science Columbia University 500 West 120 Street Room 450, Mail Code 0401 New York, NY 10027 Phone: 212-853-8400 Fax: 212-666-0140
TOPICS COURSES. If you are interested in applying a specialized Topics in Computer Science courses (COMS 4995 or COMS 6998) to your Track electives, please view Topics Courses by Track Approval.. Students may take multiple sections of COMS 4995 and/or COMS 6998, as each topic title will vary by content each semester.
To learn about PhD programs offered by Columbia's professional schools, please visit this page. A doctoral program in the Arts and Sciences is an immersive, full-time enterprise, in which students participate fully in the academic and intellectual life on campus, taking courses, conducting research in labs and libraries, teaching, attending ...
Graduate Program. The Computer Engineering Program offers a course of study leading to the degree of Master of Science (M.S.). Details about the program requirements can be found in the Computer Engineering section of the Bulletin .
Computer Science. Computer Science: MS, MS/PhD, PhD, Eng.Sc.D. ... The program is open only to Columbia University juniors with a cumulative GPA of 3.40. After earning the BS degree, students are able to seamlessly proceed toward earning their MS degree. Merging the BS and MS programs allows Columbia students to earn the MS degree in a very ...
The majors in the Department of Computer Science provide students with the appropriate computer science background necessary for graduate study or a professional career. Computers impact nearly all areas of human endeavor. ... COMS W1004 Introduction to Computer Science and Programming in Java. 3 points. ... Columbia University students may ...
Three recommendation letters. Official Graduate Record Examination (GRE) General Test Scores*. Optional for Spring and Fall 2024 applications. School Code: 2111. Personal statement. Resumé or Curriculum Vitae. Publications (optional) An interview may be requested. $85 non-refundable application fee.
Those pursuing PhD studies will work alongside world-class researchers to innovate new techniques and algorithms as they tackle hard problems across science, technology, and society. ... Department of Computer Science Columbia University 500 West 120 Street Room 450, Mail Code 0401 New York, NY 10027 Phone: 212-853-8400 Fax: 212-666-0140
PhD students in the Department of Computer Science may focus their research in the following areas: Artificial Intelligence: computer vision, decision theory/game theory, knowledge representation and reasoning, intelligent user interfaces, machine learning, natural language understanding and generation, robotics and haptics. Computer Graphics: animation, imaging, modeling, rendering ...
I completed a PhD in computer science from the University of Pennsylvania in December 1998. From January 1999 to November 2002 I was a researcher at AT&T Labs-Research, and from January 2003 until December 2010 I was an assistant/associate professor at MIT. I joined Columbia University in January 2011. I am also a research scientist at Google NYC.
The Doctor of Science in Engineering (EngScD) program is designed for motivated professionals who want to hone the skills necessary for a career in academic research. This program is particularly appropriate for working professionals who can earn a degree part-time. Learn more about the EngScD degree program. Hear about one doctoral candidate ...
PhD in Computer Science at the prestigious Columbia University is a prestigious degree that offers in-depth learning in Computer Science. Being a renowned university, Columbia University receives enough funds to ensure the best education facilities for its students across all programs. This doctorate program offered full-time primarily focuses on the practical implementation of fresh ideas ...
Students on Appointment. Minimum compensation rates for PhD students on appointment in the 2024-2025 Academic Year are currently: $48,080 for those on 12-month appointments. $42,425 for those on 9-month appointments (total compensation includes a $36,060 nine-month compensation plus a $6,365 summer stipend in June 2025). Annual Increases.
PhD Program. The student must complete the following requirements for the PhD program: Pass the Research Proficiency Evaluation (RPE) Complete the Comprehensive Course Requirement. Successfully defend the Thesis Proposal Exam. Pass the Final Doctoral Examination. Have the final thesis approved by Faculty of Graduate and Post Doctoral Studies.
Doctoral Program. For full details on the PhD programs, see the PhD Program. The UBC Department of Computer Science PhD program has four main components: Satisfying the Comprehensive Course Requirement. Passing a Research Proficiency Evaluation. Passing a Thesis Proposal Oral Examination. Completing the Research Program.
Change is accelerating. Generative AI is redefining the shape and speed of innovation. Columbia's Master of Science in Technology Management program prepares technology professionals to future-proof their practice.. Columbia University pioneered the Ivy League's first Technology Management master's program 20 years ago to empower professionals to make an economic and social impact in a ...
Computer Science Department 500 West 120 Street, Room 450 MC0401 New York, New York 10027 Main Office: +1-212-853-8400 Directions Map Directory