Computer Science

Course Listing

Computer Science

Departmental Representative:
Adam Cannon
450 Computer Science
212-939-7000
ac1076@columbia.edu

Computer Science Department: 212-939-7000

To request a syllabus, please contact the course instructor. You can find contact information for an instructor on the university directory.

COMS S1004D Introduction to Computer Science and Programming in Java. 3 points.

Columbia University students may receive credit for only one of the following two courses: 1004 and 1005.

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.

Summer 2018: COMS S1004D
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 1004 001/15855  
3 0

COMS S3134Q Data Structures in JAVA. 3 points.

Due to significant overlap, students may receive credit for only one of the following three courses: W3134, W3136, and W3137.

Prerequisites: COMS W1004 Introduction to Computer Science and Programming in Java 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.

Summer 2018: COMS S3134Q
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 3134 001/68108  
3 0

COMS S3203D Discrete Mathematics: Introduction to Combinatorics and Graph Theory. 3 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).

Summer 2018: COMS S3203D
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 3203 001/23551  
3 0

COMS S3261D Computer Science Theory. 3 points.

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.

Summer 2018: COMS S3261D
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 3261 001/74588  
3 0

COMS S3261Q Computer Science Theory. 3 points.

Prerequisites: COMS W3203 Discrete Mathematics: Introduction to Combinatorics and Graph Theory.
Corequisites: COMS W3134 Data Structures in Java, COMS W3136 Data Structures with C/C++, or COMS W3137 Honors Data Structures and Algorithms.

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.

COMS S4701D Artificial Intelligence. 3 points.

Prerequisites: COMS W3134 Data structures in Java, COMS W3136 Data Structures with C/C++, or COMS W3137 Honors Data Structures and Algorithms.

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.

Summer 2018: COMS S4701D
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 4701 001/65676  
3 0

COMS S4771D Machine Learning. 3 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.    

Summer 2018: COMS S4771D
Course Number Section/Call Number Times/Location Instructor Points Enrollment
COMS 4771 001/14639  
3 0

CSEE S3827Q Fundamentals of Computer Systems. 3 points.

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.

Summer 2018: CSEE S3827Q
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CSEE 3827 001/22335  
3 0

CSEE S4119D Computer Networks . 3 points.

Pre or Corequisites: Calculus based Probability and Statistics. 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.

Summer 2018: CSEE S4119D
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CSEE 4119 001/75804  
3 0

CSOR S4231D Analysis of Algorithms. 3 points.

Prerequisites: COMS W3134, COMS W3136, or COMS W3137, and COMS W3203.

Introduction to the design and analysis of efficient algorithms. Topics include models of computation, efficient sorting and searching, algorithms for algebraic problems, graph algorithms, dynamic programming, probabilistic methods, approximation algorithms, and NP-completeness.

Summer 2018: CSOR S4231D
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CSOR 4231 001/66892  
3 0

ENGI S1006Q Introduction to Computing for Engineers and Applied Scientists. 3 points.

An interdisciplinary course in computing intended for first year SEAS students. Introduces computational thinking, algorithmic problem solving and Python programming with applications in science and engineering. Assumes no prior programming background.

Summer 2018: ENGI S1006Q
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ENGI 1006 001/24767  
3 0

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