# Computer Science

## 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 | M W 5:30pm - 8:40pm 413 Kent Hall |
Paul Blaer | 3 | 53 |

**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 | M W 5:30pm - 8:40pm 633 Seeley W. Mudd Building |
Paul Blaer | 3 | 50 |

**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 | M W 5:30pm - 8:40pm 633 Seeley W. Mudd Building |
Robert Holliday | 3 | 31 |

**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 | T Th 1:00pm - 4:10pm 227 Seeley W. Mudd Building |
Xi Chen | 3 | 15 |

**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.

Summer 2018: COMS S3261Q | |||||

Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|

COMS 3261 | 002/63779 | M W 5:30pm - 8:40pm 413 International Affairs Bldg |
Robert Holliday | 3 | 30 |

**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 | T Th 1:00pm - 4:10pm 313 Fayerweather |
Ansaf Salleb-Aouissi | 3 | 41 |

**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 | M W 5:30pm - 8:40pm 313 Fayerweather |
German Creamer | 3 | 25 |

**COMS S4771Q 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 S4771Q | |||||

Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|

COMS 4771 | 002/75336 | T Th 1:00pm - 4:10pm 417 Mathematics Building |
Nakul Verma | 3 | 36 |

**COMS S4995D Topics in Computer Science: Methods in Unsupervised Learning. ***3 points*.

Prerequisites: COMS W4771 or equivalent

Prerequisites: Machine Learning (COMS 4771) or equivalent. Topics from unsupervised learning such as clustering and dimensionality reduction 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 of datastructures for fast Nearest Neighbor search such as Cover Trees and LSH. Algorithms will be implemented in either Matlab or Python.

Summer 2018: COMS S4995D | |||||

Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|

COMS 4995 | 001/14172 | T Th 1:00pm - 4:10pm 627 Seeley W. Mudd Building |
Nakul Verma | 3 | 20 |

**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 | T Th 5:30pm - 8:40pm 415 Schapiro Cepser |
Timothy Paine | 3 | 25 |

**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 | T Th 5:30pm - 8:40pm 633 Seeley W. Mudd Building |
Gil Zussman | 3 | 18 |

**CSEE S4824D Computer Architecture. ***3 points*.

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.

Summer 2018: CSEE S4824D | |||||

Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|

CSEE 4824 | 001/66424 | T Th 5:30pm - 8:40pm Room TBA |
Luca Carloni | 3 | 7 |

**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 | T Th 1:00pm - 4:10pm 633 Seeley W. Mudd Building |
Eleni Drinea | 3 | 7 |

**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 | T Th 5:30pm - 8:40pm 633 Seeley W. Mudd Building |
Daniel Bauer | 3 | 11 |