# Data Science

**Departmental Office:** 450 Computer Science Building; 212-939-7000

http://www.cs.columbia.edu/

**Director of Undergraduate Studies:** Dr. Jae Woo Lee, 715 CEPSR; 212-939-7066; jae@cs.columbia.edu

**Departmental Advisers:**

For updated adviser information, see http://www.cs.columbia.edu/education/undergrad/advisors.

For administrative advising issues please contact: advising@cs.columbia.edu.

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. Therefore, the department also offers courses for students who do not plan a computer science major or concentration. The computer science majors offer maximum flexibility by providing students with a range of options for program specialization. The department offers four majors: computer science; information science; data science; and computer science-mathematics, offered jointly with the Mathematics Department.

## Computer Science Major

Students study a common core of fundamental topics, supplemented by a track that identifies specific areas for deeper study. The foundations track prepares students for advanced work in fundamental, theoretical, and mathematical aspects of computing, including analysis of algorithms, scientific computing, and security. The systems track prepares students for immediate employment in the computer industry as well as advanced study in software engineering, operating systems, computer-aided digital design, computer architecture, programming languages, and user interfaces. The intelligent systems track provides specialization for the student interested in natural language processing and systems capable of exhibiting “human-like” intelligence. The applications track is for students interested in the implementation of interactive multimedia content for the Internet and wireless applications. The vision, graphics, interaction, and robotics track exposes students to computer vision, graphics, human-computer interaction, and robotics.

A combination track is available to students who wish to pursue an interdisciplinary course of study combining computer science and another field in the arts, humanities, mathematics, natural sciences, or social sciences. A student planning a combination track should be aware that one additional course is required to complete this option.

## Information Science Major

Information science is an interdisciplinary major designed to provide a student with an understanding of how information is organized, accessed, stored, distributed, and processed in strategic segments of today’s society. Recent years have seen an explosive growth of on-line information, with people of all ages and all walks of life making use of the World Wide Web and other information in digital form.

This major puts students at the forefront of the information revolution, studying how on-line access touches on all disciplines and changing the very way people communicate. Organizations have large stores of in-house information that are crucial to their daily operation. Today’s systems must enable quick access to relevant information, must ensure that confidential information is secure, and must enable new forms of communication among people and their access to information.

The information science major can choose a scientific focus on algorithms and systems for organizing, accessing, and processing information, or an interdisciplinary focus in order to develop an understanding of, and tools for, information modeling and use within an important sector of modern society such as economics or health.

## Advanced Placement

The department grants 3 points for a score of 4 or 5 on the AP Computer Science exam along with exemption from COMS W1004 Introduction to Computer Science and Programming in Java. However, we still recommend that you take COMS W1004 or W1007 even if you have credits from the CS AP exam. COMS W1007 Honors Introduction to Computer Science is recommended if you scored 5 on the AP exam, and COMS W1004 is recommended if you scored 4.

## Pre-Introductory Courses

COMS W1004 is the first course in the Computer Science major curriculum, and it does not require any previous computing experience. Before taking COMS W1004, however, students have an option to start with one of the pre-introductory courses: ENGI E1006 or COMS W1002.

ENGI E1006 Introduction to Computing for Engineers and Applied Scientist is a general introduction to computing for STEM students. ENGI E1006 is in fact a required course for all engineering students. COMS W1002 Computing In Context is a course primarily intended for humanities majors, but it also serves as a pre-introductory course for CS majors. ENGI E1006 and COMS W1002 do not count towards Computer Science major.

## Laboratory Facilities

The department has well-equipped lab areas for research in computer graphics, computer-aided digital design, computer vision, databases and digital libraries, data mining and knowledge discovery, distributed systems, mobile and wearable computing, natural language processing, networking, operating systems, programming systems, robotics, user interfaces, and real-time multimedia.

Research labs contain several large Linux and Solaris clusters; Puma 500 and IBM robotic arms; a UTAH-MIT dexterous hand; an Adept-1 robot; three mobile research robots; a real-time defocus range sensor; interactive 3-D graphics workstations with 3-D position and orientation trackers; prototype wearable computers, wall-sized stereo projection systems; see-through head-mounted displays; a networking testbed with three Cisco 7500 backbone routers, traffic generators; an IDS testbed with secured LAN, Cisco routers, EMC storage, and Linux servers; and a simulation testbed with several Sun servers and Cisco Catalyst routers.The department uses a SIP IP phone system. The protocol was developed in the department.

The department's computers are connected via a switched 1Gb/s Ethernet network, which has direct connectivity to the campus OC-3 Internet and internet 2 gateways. The campus has 802.11b/g wireless LAN coverage.

The research facility is supported by a full-time staff of professional system administrators and programmers.

## Professors

- Alfred V. Aho
- Peter K. Allen
- Peter Belhumeur
- Steven M. Bellovin
- David Blei
- Luca Carloni
- Michael J. Collins
- Steven K. Feiner
- Luis Gravano
- Julia Hirschberg
- Gail E. Kaiser
- John R. Kender
- Kathleen R. McKeown
- Vishal Misra
- Shree K. Nayar
- Jason Nieh
- Steven M. Nowick

Christos Papadimitriou - Kenneth A. Ross
- Henning G. Schulzrinne
- Rocco A. Servedio
- Salvatore J. Stolfo
- Jeannette Wing
- Mihalis Yannakakis

## Associate Professors

- Alexandr Andoni
- Augustin Chaintreau
- Xi Chen
- Stephen A. Edwards
- Yaniv Erlich
- Roxana Geambasu
- Eitan Grinspun
- Daniel Hsu
- Tony Jebara
- Martha Allen Kim
- Tal Malkin
- Itsik Pe'er
- Daniel S. Rubenstein
- Simha Sethumadhavan
- Junfeng Yang
- Changxi Zheng

## Assistant Professors

- Lydia Chilton
- Ronghui Gu
- Suman Jana
- Baishakhi Ray
- Carl Vondrick
- Omri Weinstein
- Eugene Wu

## Senior Lecturer in Discipline

- Paul Blaer
- Adam Cannon
- Jae Woo Lee

## Lecturer in Discipline

- Daniel Bauer
- Tony Dear
- Ansaf Salleb-Aouissi
- Nakul Verma

## Associated Faculty Joint

- Shih-Fu Chang
- Clifford Stein

## Associated Faculty

- Matei Ciocarlie
- Edward G. Coffman Jr.
*(emeritus)* - Eleni Drinea
- Jonathan Gross (
*emeritus*) - Andreas Mueller
- Steven H. Unger (
*emeritus*) - Vladimir Vapnik
- Yechiam Yemini (
*emeritus*)

## Senior Research Scientists

- Moti Yung

## Research Scientists

- Smaranda Muresan*

## Associated Research Scientists

- Allison Breton Bishop
- Giuseppe DiGuglielmo
- Paolo Mantovani
- Hiroshi Sasaki
- Eran Tromer

## Professor of Practice

- Donald F. Ferguson

## Guidelines for all Computer Science Majors and Minors

### Courses

Students may receive credit for only one of the following two courses:

- COMS W1004 Introduction to Computer Science and Programming in Java
- COMS W1005 Introduction to Computer Science and Programming in MATLAB.

Students may receive credit for only one of the following three courses:

- COMS W3134 Data Structures in Java
- COMS W3136 Data Structures with C/C++
- COMS W3137 Honors Data Structures and Algorithms

However, COMS W1005 and COMS W3136 cannot be counted towards the Computer Science major, minor, and concentration.

### Transfer Credit

As a rule, no more than 12 transfer credits are accepted toward the major.

### Grading

Courses in which the student receives the grade of D may not be counted toward the major requirement or the minor option.

## Guidelines for all Computer Science Majors and Concentrators

### Courses

Students may receive credit for only one of the following two courses:

- COMS W1004 Introduction to Computer Science and Programming in Java
- COMS W1005 Introduction to Computer Science and Programming in MATLAB.

Students may receive credit for only one of the following three courses:

- COMS W3134 Data Structures in Java
- COMS W3136 Data Structures with C/C++
- COMS W3137 Honors Data Structures and Algorithms

However, COMS W1005 and COMS W3136 cannot be counted towards the Computer Science major, minor, and concentration.

### Transfer Credit

As a rule, no more than 12 transfer credits are accepted toward the major.

### Grading

A maximum of one course worth no more than 4 points passed with a grade of D may be counted toward the major or concentration.

## Major in Computer Science

Please read *Guidelines for all Computer Science Majors and Concentrators* above.

Please read *Guidelines for all Computer Science Majors and Concentrators* above.

Please read *Guidelines for all Computer Science Majors and Minors* above.

All majors should confer with their program adviser each term to plan their programs of study. Students considering a major in computer science are encouraged to talk to a program adviser during their first or second year. A typical program of study is as follows:

### Program of Study

#### Computer Science Core (22-24 points)

##### For students who declare in Spring 2014 and beyond:

Code | Title | Points |
---|---|---|

ENGI E1006 | Introduction to Computing for Engineers and Applied Scientists (recommended but not required) | |

First Year | ||

COMS W1004 | Introduction to Computer Science and Programming in Java | |

or COMS W1007 | Honors Introduction to Computer Science | |

Sophomore Year | ||

COMS W3134 | Data Structures in Java | |

or COMS W3137 | Honors Data Structures and Algorithms | |

COMS W3157 | Advanced Programming | |

COMS W3203 | Discrete Mathematics: Introduction to Combinatorics and Graph Theory | |

Junior and Senior Year | ||

Select the remaining required core courses: | ||

COMS W3261 | Computer Science Theory | |

CSEE W3827 | Fundamentals of Computer Systems | |

Select one of the following courses: | ||

MATH UN2010 | Linear Algebra | |

APMA E2101 | Introduction to Applied Mathematics | |

APMA E3101 | Linear Algebra | |

STAT GU4001 | Introduction to Probability and Statistics |

##### For students who declared prior to Spring 2014:

Code | Title | Points |
---|---|---|

First Year | ||

COMS W1004 | Introduction to Computer Science and Programming in Java | |

Sophomore Year | ||

COMS W1007 | Honors Introduction to Computer Science | |

COMS W3137 | Honors Data Structures and Algorithms | |

COMS W3157 | Advanced Programming | |

COMS W3203 | Discrete Mathematics: Introduction to Combinatorics and Graph Theory | |

Junior and Senior Year | ||

COMS W3261 | Computer Science Theory | |

CSEE W3827 | Fundamentals of Computer Systems |

In addition to the CS Core (22-24 points), all CS majors must complete the Calculus Requirement (3 points) and a Track Requirement (15 or 18 points). The CS major therefore requires 40-45 points total.

#### Mathematics (3 points)

Calculus II or Calculus III.

Note that Calculus III does NOT depend on Calculus II. You can take either Calculus II or III, but we recommend Calculus III, which covers topics that are a bit more relevant for upper-¬level Computer Science courses.

If you have received equivalent credits for Calculus I & II already (through a 4 or 5 on the AP Calculus exam for example), you are not required to take any more Calculus courses. But we recommend taking one more semester of Calculus, either Math UN1201 Calculus III or APAM E2000 Multivariate Calculus for Engineers and Scientists. APAM E2000 covers relevant topics from Calculus III and IV.

#### Track Requirement (15 or 18 points)

Students must select one of the following six upper-level tracks. Each track, except the combination track, requires five courses consisting of required, elective breadth, and elective track courses. The combination track requires a selection of six advanced courses: three *3000*- or *4000*-level computer science courses and three *3000*- or *4000*-level courses from another field. The elective breadth requirement in each track can be fulfilled with any 3-point computer science *3000*-level or higher course that is not a computer science core course or a technical elective course in that track. In addition to the breadth elective, the track requirements are as follows:

##### Foundations Track (15 points)

For students interested in algorithms, computational complexity, and other areas of theoretical Computer Science.

Note: Students who declared their Computer Science major prior to Fall 2016 may also count COMS 4241, COMS 4205, COMS 4281, COMS 4444, COMS 4771, and COMS 4772 as track elective courses.

Code | Title | Points |
---|---|---|

Required Courses | ||

CSOR W4231 | Analysis of Algorithms I | |

COMS W4236 | Introduction to Computational Complexity | |

Track Electives | ||

Select 2 from: | ||

MATH UN3020 | Number Theory and Cryptography | |

MATH UN3025 | Making, Breaking Codes | |

COMS W4203 | Graph Theory | |

MATH GU4032 | Fourier Analysis | |

MATH GU4041 | INTRO MODERN ALGEBRA I | |

MATH GU4042 | INTRO MODERN ALGEBRA II | |

MATH GU4061 | INTRO MODERN ANALYSIS I | |

MATH GU4155 | Probability Theory | |

COMS W4252 | Introduction to Computational Learning Theory | |

COMS W4261 | Introduction to Cryptography | |

APMA E4300 | Computational Math: Introduction to Numerical Methods | |

IEOR E4407 | Game Theoretic Models of Operations | |

CSPH G4802 | ||

COMS E6232 | Analysis of Algorithms, II | |

MATH G6238 | Enumerative Combinatorics | |

COMS E6253 | Advanced Topics in Computational Learning Theory | |

COMS E6261 | Advanced Cryptography | |

EEOR E6616 | Convex optimization | |

IEOR E6613 | Optimization, I | |

IEOR E6614 | Optimization, II | |

IEOR E6711 | Stochastic models, I | |

IEOR E6712 | Stochastic models, II | |

ELEN E6717 | Information theory | |

ELEN E6718 | Error Correcting Codes: Classical and Modern | |

Adviser Approved: | ||

COMS W3902 | Undergraduate Thesis | |

COMS W3998 | Undergraduate Projects in Computer Science | |

COMS W4901 | Projects in Computer Science | |

COMS W4995 | Special topics in computer science, I | |

COMS E6998 | Topics in Computer Science | |

One Breadth Course | ||

Any 3-point COMS 3000- or 4000-level course except those courses in the CS core or in the required or elective courses for this track |

##### Software Systems Track (15 points)

For students interested in networks, programming languages, operating systems, software engineering, databases, security, and distributed systems.

Code | Title | Points |
---|---|---|

Required Courses | ||

COMS W4115 | Programming Languages and Translators | |

COMS W4118 | Operating Systems I | |

CSEE W4119 | COMPUTER NETWORKS | |

Track Electives | ||

Select 1 from: | ||

Any COMS W41xx course | ||

COMS W4444 | Programming and Problem Solving | |

Any COMS W48xx course | ||

Adviser Approved: | ||

COMS W3902 | Undergraduate Thesis | |

COMS W3998 | Undergraduate Projects in Computer Science | |

COMS W4901 | Projects in Computer Science | |

COMS W4995 | Special topics in computer science, I | |

COMS W4996 | Special topics in computer science, II | |

Any COMS E68XX course | ||

Any COMS E61XX course | ||

One Breadth Course | ||

Any 3-point COMS 3000- or 4000-level course except those courses in the CS core or in the required or elective courses for this track |

##### Intelligent Systems Track (15 points)

For students interested in machine learning, robotics, and systems capable of exhibiting “human-like” intelligence.

Code | Title | Points |
---|---|---|

Required Courses | ||

Select two of the following courses: | ||

COMS W4701 | Artificial Intelligence | |

COMS W4705 | Natural Language Processing | |

COMS W4706 | Spoken Language Processing | |

COMS W4731 | Computer Vision | |

COMS W4733 | Computational Aspects of Robotics | |

COMS W4771 | Machine Learning | |

Track Electives | ||

Select 2 from: | ||

COMS W4252 | Introduction to Computational Learning Theory | |

Any COMS W47xx course | ||

Any COMS E67XX course | ||

Adviser Approved: | ||

COMS W3902 | Undergraduate Thesis | |

COMS W3998 | Undergraduate Projects in Computer Science | |

COMS W4901 | Projects in Computer Science | |

COMS W4995 | Special topics in computer science, I | |

COMS E6998 | Topics in Computer Science | |

One Breadth Course | ||

Any 3-point COMS 3000- or 4000-level course except those courses in the CS core or in the required or elective courses for this track |

##### Applications Track (15 points)

For students interested in the implementation of interactive multimedia applications for the internet and wireless networks.

Code | Title | Points |
---|---|---|

Required Courses | ||

COMS W4115 | Programming Languages and Translators | |

COMS W4170 | User Interface Design | |

Track Electives | ||

Select 2 from: | ||

Any COMS W41xx course | ||

Any COMS W47xx course | ||

Adviser Approved: | ||

COMS W3902 | Undergraduate Thesis | |

COMS W3998 | Undergraduate Projects in Computer Science | |

COMS W4901 | Projects in Computer Science | |

COMS W4995 | Special topics in computer science, I | |

Any COMS E69XX course | ||

One Breadth Course | ||

##### Vision, Graphics, Interaction, and Robotics Track (15 points)

For students in the vision, interaction, graphics, and robotics track. It focuses on visual information with topics in vision, graphics, human-computer interaction, robotics, modeling, and learning. Students learn about fundamental ways in which visual information is captured, manipulated, and experienced.

Code | Title | Points |
---|---|---|

Required Courses | ||

Select two of the following courses: | ||

COMS W4160 | Computer Graphics | |

COMS W4167 | Computer Animation | |

COMS W4731 | Computer Vision | |

Track Electives | ||

Select 2 from: | ||

COMS W4162 | Advanced Computer Graphics | |

COMS W4170 | User Interface Design | |

COMS W4172 | 3D User Interfaces and Augmented Reality | |

COMS W4701 | Artificial Intelligence | |

COMS W4733 | Computational Aspects of Robotics | |

COMS W4735 | Visual Interfaces to Computers | |

COMS W4771 | Machine Learning | |

Adviser Approved: | ||

COMS W3902 | Undergraduate Thesis | |

COMS W3998 | Undergraduate Projects in Computer Science | |

COMS W4901 | Projects in Computer Science | |

COMS W4995 | Special topics in computer science, I | |

Any COMS E69XX course | ||

One Breadth Course | ||

##### Combination Track (18 points)

For students who wish to combine computer science with another discipline in the arts, humanities, social or natural sciences. A coherent selection of six upper-level courses is required: three from computer science and three from another discipline.

The courses should be planned with and approved by the student’s CS faculty advisor by the first semester of the junior year. The six courses are typically 4000-level elective courses that would count towards the individual majors. Moreover, the six courses should have a common theme. The combination track is not intended for those students who pursue double majors.

## Major in Computer Science—Mathematics

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 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.

## Major in Information Science

Please read *Guidelines for all Computer Science Majors and Concentrators* above.

The major in information science requires a minimum of 33 points including a core requirement of five courses.

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.

### Core Requirement

Code | Title | Points |
---|---|---|

COMS W1001 | Introduction to Information Science | |

or COMS W1002 Computing in Context | ||

COMS W1004 | Introduction to Computer Science and Programming in Java | |

COMS W1007 | Honors Introduction to Computer Science | |

COMS W3134 | Data Structures in Java | |

STAT GU4001 | Introduction to Probability and Statistics |

Following are some suggested programs of instruction:

### Information Science and Contemporary Society

Students may focus on how humans use technology and how technology has changed society.

The requirements include:

Code | Title | Points |
---|---|---|

COMS W4111 | INTRODUCTION TO DATABASES | |

COMS W4170 | User Interface Design | |

COMS W4701 | Artificial Intelligence | |

COMS W3410 | Computers and Society | |

SOCI UN3010 | Methods for Social Research | |

SOCI UN3960 | Law, Science, and Society |

### Information Science and the Economy

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.

The requirements include:

Code | Title | Points |
---|---|---|

COMS W4111 | INTRODUCTION TO DATABASES | |

COMS W4701 | Artificial Intelligence | |

COMS W4771 | Machine Learning | |

ECON UN3412 | Introduction To Econometrics | |

ECON UN3025 | Financial Economics | |

ECON UN3265 | MONEY AND BANKING |

### Information Science and Health Sciences

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.

The requirements include:

Code | Title | Points |
---|---|---|

COMS W4111 | INTRODUCTION TO DATABASES | |

COMS W4170 | User Interface Design | |

COMS W4701 | Artificial Intelligence | |

BINF G4001 | ||

BIOL W4037 | Bioinformatics of Gene Expression | |

ECBM E3060/E4060 | Introduction to genomic information science and technology |

## Major in Data Science

Please read *Guidelines for all Computer Science Majors and Concentrators* above.

In response to the ever growing importance of "big data" in scientific and policy endeavors, the last few years have seen an 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) | ||

MATH UN1101 | CALCULUS I | |

MATH UN1102 | Calculus II | |

MATH UN1201 | Calculus III | |

MATH UN2010 | Linear Algebra | |

This introductory Statistics course: | ||

STAT UN1201 | Calculus-Based Introduction to Statistics | |

Statistics (12 points) | ||

STAT GU4203 | PROBABILITY THEORY | |

STAT GU4204 | Statistical Inference | |

STAT GU4205 | Linear Regression Models | |

STAT GU4241 | Statistical Machine Learning | |

or COMS W4771 Machine Learning | ||

Computer Science (12 points) | ||

Select one of the following courses: | ||

COMS W1004 | Introduction to Computer Science and Programming in Java | |

COMS W1005 | Introduction to Computer Science and Programming in MATLAB | |

COMS W1007 | Honors Introduction to Computer Science | |

ENGI E1006 | Introduction to Computing for Engineers and Applied Scientists | |

Select one of the following courses: | ||

COMS W3134 | Data Structures in Java | |

COMS W3136 | Data Structures with C/C++ | |

COMS W3137 | Honors Data Structures and Algorithms | |

Two required courses: | ||

COMS W3203 | Discrete Mathematics: Introduction to Combinatorics and Graph Theory | |

CSOR W4231 | Analysis of Algorithms I | |

Electives (15 points) | ||

Select two of the following courses: | ||

STAT UN3106 | Applied Data Mining | |

STAT GU4206 | Statistical Computing and Introduction to Data Science | |

STAT GU4224 | BAYESIAN STATISTICS | |

STAT GU4243 | Applied Data Science | |

STAT Q4242 | Advanced Machine Learning | |

Select three of the following courses: | ||

COMS W3261 | Computer Science Theory | |

COMS W4111 | INTRODUCTION TO DATABASES | |

COMS W4130 | Principles and Practice of Parallel Programming | |

COMS W4236 | Introduction to Computational Complexity | |

COMS W4252 | Introduction to Computational Learning Theory | |

Any COMS W47xx course EXCEPT W4771 |

## Minor in Computer Science

Please read *Guidelines for all Computer Science Majors and Minors* above.

**For students who declare in Spring 2014 and beyond:**

The minor in computer science requires a minimum of 22-24 points, as follows:

Code | Title | Points |
---|---|---|

COMS W1004 | Introduction to Computer Science and Programming in Java | |

or COMS W1007 | Honors Introduction to Computer Science | |

COMS W3203 | Discrete Mathematics: Introduction to Combinatorics and Graph Theory | |

COMS W3134 | Data Structures in Java | |

or COMS W3137 | Honors Data Structures and Algorithms | |

COMS W3157 | Advanced Programming | |

COMS W3261 | Computer Science Theory | |

CSEE W3827 | Fundamentals of Computer Systems (or any 3 point 4000-level computer science course) | |

Select one of the following courses: | ||

MATH UN2010 | Linear Algebra | |

APMA E2101 | Introduction to Applied Mathematics | |

APMA E3101 | Linear Algebra | |

MATH V2020 | Honors Linear Algebra | |

STAT GU4001 | Introduction to Probability and Statistics | |

SIEO W3600 |

**For students who declared prior to Spring 2014:**

The minor requires a minimum of 23 points, as follows:

Code | Title | Points |
---|---|---|

COMS W1004 | Introduction to Computer Science and Programming in Java | |

COMS W1007 | Honors Introduction to Computer Science | |

COMS W3137 | Honors Data Structures and Algorithms | |

COMS W3157 | Advanced Programming | |

COMS W3261 | Computer Science Theory | |

CSEE W3827 | Fundamentals of Computer Systems (or any 3-point 4000-level computer science course) |

## Concentration in Computer Science

Please read *Guidelines for all Computer Science Majors and Concentrators* above.

**For students who declare in Spring 2014 and beyond:**

The concentration in computer science requires a minimum of 22-24 points, as follows:

Code | Title | Points |
---|---|---|

COMS W1004 | Introduction to Computer Science and Programming in Java | |

or COMS W1007 | Honors Introduction to Computer Science | |

COMS W3134 | Data Structures in Java | |

or COMS W3137 | Honors Data Structures and Algorithms | |

COMS W3157 | Advanced Programming | |

COMS W3203 | Discrete Mathematics: Introduction to Combinatorics and Graph Theory | |

COMS W3261 | Computer Science Theory | |

CSEE W3827 | Fundamentals of Computer Systems (or any 3 point 4000-level computer science course) | |

Select one of the following courses: | ||

MATH UN2010 | Linear Algebra | |

MATH V2020 | Honors Linear Algebra | |

APMA E2101 | Introduction to Applied Mathematics | |

APMA E3101 | Linear Algebra | |

STAT GU4001 | Introduction to Probability and Statistics | |

SIEO W3600 |

**For students who declared prior to Spring 2014:**

The concentration requires a minimum of 23 points, as follows:

Code | Title | Points |
---|---|---|

COMS W1004 | Introduction to Computer Science and Programming in Java | |

COMS W1007 | Honors Introduction to Computer Science | |

COMS W3137 | Honors Data Structures and Algorithms | |

COMS W3157 | Advanced Programming | |

COMS W3261 | Computer Science Theory | |

CSEE W3827 | Fundamentals of Computer Systems (or any 3-point 4000-level computer science course) |

## Computer Science

**COMS W1001 Introduction to Information Science.** *3 points*.

Lect: 3.

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 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.

Fall 2020: COMS W1002 |
|||||

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

COMS 1002 | 001/11682 | T Th 2:40pm - 3:55pm Online Only |
Adam Cannon | 4 | 274/300 |

**COMS W1004 Introduction to Computer Science and Programming in Java.** *3 points*.

Lect: 3.

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*.

Fall 2020: COMS W1004 |
|||||

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

COMS 1004 | 001/11692 | T Th 4:10pm - 5:25pm Online Only |
Adam Cannon | 3 | 284/400 |

**COMS W1005 Introduction to Computer Science and Programming in MATLAB.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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 W1007 Honors Introduction to Computer Science.** *3 points*.

Lect: 3.

Prerequisites: AP Computer Science with a grade of 4 or 5 or similar experience.

An honors-level introduction to computer science, intended primarily for students considering a major in computer science. Computer science as a science of abstraction. Creating models for reasoning about and solving problems. The basic elements of computers and computer programs. Implementing abstractions using data structures and algorithms. Taught in Java.

**COMS W1404 Emerging Scholars Program Seminar.** *1 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.

**COMS W3101 Programming Languages.** *1 point*.

Lect: 1.

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 Technologies.** *1-2 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.

**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

Fall 2020: COMS W3107 |
|||||

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

COMS 3107 | 001/15932 | M W 1:10pm - 2:25pm Online Only |
John Kender | 3.00 | 50/70 |

**COMS W3134 Data Structures in Java.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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*.

Fall 2020: COMS W3134 |
|||||

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

COMS 3134 | 001/10066 | M W 5:40pm - 6:55pm Online Only |
Paul Blaer | 3 | 333/400 |

**COMS W3136 Data Structures with C/C++.** *4 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.

**COMS W3137 Honors Data Structures and Algorithms.** *4 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 points*.

Lect: 4.

Prerequisites: (COMS W3134) or (COMS W3137)

C programming language and Unix systems programming. Also covers Git, Make, TCP/IP networking basics, C++ fundamentals.

Fall 2020: COMS W3157 |
|||||

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

COMS 3157 | 001/10067 | T Th 4:10pm - 5:25pm Online Only |
Jae Lee | 4 | 404/500 |

**COMS W3203 Discrete Mathematics: Introduction to Combinatorics and Graph Theory.** *3 points*.

Lect: 3.

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).

Fall 2020: COMS W3203 |
|||||

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

COMS 3203 | 001/11672 | T Th 10:10am - 11:25am Online Only |
Ansaf Salleb-Aouissi | 3 | 150/150 |

COMS 3203 | 002/11673 | T Th 11:40am - 12:55pm Online Only |
Ansaf Salleb-Aouissi | 3 | 150/150 |

**COMS W3210 Scientific Computation.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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 points*.

CC/GS: Partial Fulfillment of Science Requirement

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.

Fall 2020: COMS W3261 |
|||||

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

COMS 3261 | 001/11666 | T Th 8:40am - 9:55am Online Only |
Tal Malkin | 3 | 180/170 |

COMS 3261 | 002/11667 | T Th 10:10am - 11:25am Online Only |
Tal Malkin | 3 | 194/185 |

COMS 3261 | R01/22802 | F 10:10am - 12:00pm Online Only |
Tal Malkin | 3 | 0/170 |

COMS 3261 | R02/22803 | F 12:10pm - 2:00pm Online Only |
Tal Malkin | 3 | 0/170 |

**COMS W3410 Computers and Society.** *3 points*.

Lect: 3.

Broader impact of computers. Social networks and privacy. Employment, intellectual property, and the media. Science and engineering ethics. Suitable for nonmajors.

Fall 2020: COMS W3410 |
|||||

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

COMS 3410 | 001/11022 | T Th 4:10pm - 5:25pm Online Only |
Ronald Baecker | 3 | 60/60 |

**COMS W3902 Undergraduate Thesis.** *1-6 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*.

Lect: 3.

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 Undergraduate Projects in Computer Science.** *1-3 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, but not for a total of more than 3 points of degree credit. Consult the department for section assignment.

**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

Prerequisites: (COMS W3134) or (COMS W3137) or (COMS W3136) and fluency in Java); or the instructor's permission. 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

Fall 2020: COMS W4111 |
|||||

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

COMS 4111 | 001/10069 | T Th 1:10pm - 2:25pm Online Only |
Luis Gravano | 3.00 | 151/175 |

COMS 4111 | 002/10873 | F 10:10am - 12:40pm 417 International Affairs Bldg |
Donald Ferguson | 3.00 | 184/200 |

COMS 4111 | 003/10874 | T Th 10:10am - 12:40pm Online Only |
Alexandros Biliris | 3.00 | 35/100 |

COMS 4111 | R02/22805 | Sa 10:00am - 12:00pm 417 International Affairs Bldg |
Donald Ferguson | 3.00 | 4/200 |

COMS 4111 | V03/21543 | |
Alexandros Biliris | 3.00 | 10/99 |

**COMS W4112 Database System Implementation.** *3 points*.

Lect: 2.5.

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 Fundamentals of Large-Scale Distributed Systems.** *3 points*.

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.

Fall 2020: COMS W4113 |
|||||

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

COMS 4113 | 001/11671 | F 1:10pm - 3:40pm Online Only |
Roxana Geambasu | 3 | 164/150 |

COMS 4113 | V01/21545 | |
Roxana Geambasu | 3 | 14/99 |

**COMS W4115 Programming Languages and Translators.** *3 points*.

Lect: 3.

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.

Fall 2020: COMS W4115 |
|||||

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

COMS 4115 | 001/10070 | M W 1:10pm - 2:25pm Online Only |
Baishakhi Ray | 3 | 101/100 |

**COMS W4117 Compilers and Interpreters.** *3 points*.

Lect: 3.**Not offered during 2020-21 academic year.**

Prerequisites: (COMS W4115) or instructor's permission.

Continuation of *COMS W4115*, with broader and deeper investigation into the design and implementation of contemporary language translators, be they compilers or interpreters. Topics include parsing, semantic analysis, code generation and optimization, run-time environments, and compiler-compilers. A programming project is required.

**COMS W4118 Operating Systems I.** *3 points*.

Lect: 3.

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.

Fall 2020: COMS W4118 |
|||||

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

COMS 4118 | 001/10071 | W 4:10pm - 6:40pm 309 Havemeyer Hall |
Jae Lee | 3 | 82/150 |

COMS 4118 | R01/22806 | Sa 11:40am - 12:55pm 301 Pupin Laboratories |
Jae Lee | 3 | 0/150 |

COMS 4118 | V01/21548 | |
Jae Lee | 3 | 4/99 |

**COMS W4121 Computer Systems for Data Science.** *3 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 W4130 Principles and Practice of Parallel Programming.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

Prerequisites: (COMS W3134 or COMS W3137 or COMS W3136 and experience in Java) and basic understanding of analysis of algorithms.

Principles of parallel software design. Topics include task and data decomposition, load-balancing, reasoning about correctness, determinacy, safety, and deadlock-freedom. Application of techniques through semester-long design project implementing performant, parallel application in a modern parallel programming language.

**COMS W4156 Advanced Software Engineering.** *3 points*.

Lect: 3.

Prerequisites: (COMS W3157) or equivalent.

Software lifecycle using frameworks, libraries and services. Major emphasis on software testing. Centers on a team project.

Fall 2020: COMS W4156 |
|||||

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

COMS 4156 | 001/10072 | T Th 10:10am - 11:25am Online Only |
Gail Kaiser | 3 | 109/120 |

COMS 4156 | V01/21552 | |
Gail Kaiser | 3 | 7/99 |

**COMS W4160 Computer Graphics.** *3 points*.

Lect: 3.

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.

**COMS W4162 Advanced Computer Graphics.** *3 points*.

Lect: 3.

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 W4167 Computer Animation.** *3 points*.

Lect: 3.

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).

Fall 2020: COMS W4167 |
|||||

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

COMS 4167 | 001/11388 | T Th 5:40pm - 6:55pm 451 Computer Science Bldg |
Changxi Zheng | 3 | 69/70 |

COMS 4167 | V01/22364 | |
Changxi Zheng | 3 | 1/99 |

**COMS W4170 User Interface Design.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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.

Fall 2020: COMS W4170 |
|||||

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

COMS 4170 | 001/10073 | M W 2:40pm - 3:55pm 614 Schermerhorn Hall |
Brian Smith | 3 | 86/110 |

**COMS W4172 3D User Interfaces and Augmented Reality.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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.

**COMS W4181 Security I.** *3 points*.

**Not offered during 2020-21 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.

Fall 2020: COMS W4181 |
|||||

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

COMS 4181 | 001/10074 | T Th 1:10pm - 2:25pm Online Only |
Steven Bellovin | 3 | 110/100 |

COMS 4181 | V01/21553 | |
Steven Bellovin | 3 | 3/99 |

**COMS W4182 Security II.** *3 points*.

**Not offered during 2020-21 academic year.**

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 esting and fuzzing. Blockchain. Human security issues.

**COMS W4186 Malware Analysis and Reverse Engineering.** *3 points*.

**Not offered during 2020-21 academic year.**

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.

Fall 2020: COMS W4186 |
|||||

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

COMS 4186 | 001/22036 | Th 4:10pm - 6:40pm 313 Fayerweather |
Michael Sikorski | 3 | 16/60 |

**COMS W4203 Graph Theory.** *3 points*.

Lect: 3.

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.

**COMS W4205 Combinatorial Theory.** *3 points*.

Lect: 3.**Not offered during 2020-21 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 W4232 Advanced Algorithms.** *3 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.

**COMS W4236 Introduction to Computational Complexity.** *3 points*.

Lect: 3.

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.

Fall 2020: COMS W4236 |
|||||

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

COMS 4236 | 001/11562 | F 4:10pm - 6:40pm Online Only |
Xi Chen | 3 | 35/40 |

COMS 4236 | V01/21554 | |
Xi Chen | 3 | 5/99 |

**COMS W4241 Numerical Algorithms and Complexity.** *3 points*.

Lect: 3.

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 Numerical Algorithms and Their Complexity II.** *3 points*.

Prerequisites: *COMS W4241*.

A continuation of *COMS W4241.*

**COMS W4252 Introduction to Computational Learning Theory.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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 Introduction to Cryptography.** *3 points*.

Lect: 2.5.

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 Introduction to Quantum Computing.** *3 points*.

Lect: 3.

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.

**COMS W4419 Internet Technology, Economics, and Policy.** *3 points*.

**Not offered during 2020-21 academic year.**

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.

Fall 2020: COMS W4419 |
|||||

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

COMS 4419 | 001/10075 | F 1:10pm - 3:40pm Online Only |
Henning Schulzrinne | 3 | 42/80 |

**COMS W4444 Programming and Problem Solving.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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.

Fall 2020: COMS W4444 |
|||||

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

COMS 4444 | 001/10315 | M W 1:10pm - 2:25pm Online Only |
Kenneth Ross | 3 | 0/30 |

**COMS W4460 Principles of Innovation and Entrepreneurship.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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.

**COMS W4560 Introduction to Computer Applications in Health Care and Biomedicine.** *3 points*.

Lect: 3.

Prerequisites: Experience with computers and a passing familiarity with medicine and biology. Undergraduates in their senior or junior years may take this course only if they have adequate background in mathematics and receive the instructor's permission.

An overview of the field of biomedical informatics, combining perspectives from medicine, computer science and social science. Use of computers and information in health care and the biomedical sciences, covering specific applications and general methods, current issues, capabilities and limitations of biomedical informatics. Biomedical Informatics studies the organization of medical information, the effective management of information using computer technology, and the impact of such technology on medical research, education, and patient care. The field explores techniques for assessing current information practices, determining the information needs of health care providers and patients, developing interventions using computer technology, and evaluating the impact of those interventions.

**COMS W4701 Artificial Intelligence.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

Prerequisites: (COMS W3134 or COMS W3136 or COMS W3137) and any course on probability. 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.

Fall 2020: COMS W4701 |
|||||

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

COMS 4701 | 001/10076 | M W 4:10pm - 6:40pm Online Only |
Tony Dear | 3 | 140/150 |

COMS 4701 | 002/21411 | T Th 4:10pm - 6:40pm Online Only |
Tony Dear | 3 | 100/150 |

COMS 4701 | V01/21555 | |
Tony Dear | 3 | 13/99 |

**COMS W4705 Natural Language Processing.** *3 points*.

Lect: 3.

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.

Fall 2020: COMS W4705 |
|||||

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

COMS 4705 | 001/14312 | M W 4:10pm - 5:25pm Online Only |
Daniel Bauer | 3 | 176/200 |

COMS 4705 | 002/22057 | M 10:10am - 12:40pm 309 Havemeyer Hall |
Yassine Benajiba | 3 | 50/175 |

COMS 4705 | 002/22057 | F 1:10pm - 3:40pm 417 International Affairs Bldg |
Yassine Benajiba | 3 | 50/175 |

**COMS W4706 Spoken Language Processing.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

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 W4725 Knowledge representation and reasoning.** *3 points*.

Lect: 3.**Not offered during 2020-21 academic year.**

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.** *3 points*.

Lect: 3.

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.

**COMS W4733 Computational Aspects of Robotics.** *3 points*.

CC/GS: Partial Fulfillment of Science Requirement

Prerequisites: (COMS W3134 or COMS W3136COMS W3137)

Introduction to robotics from a computer science perspective. Topics include coordinate frames and kinematics, computer architectures for robotics, integration and use of sensors, world modeling systems, design and use of robotic programming languages, and applications of artificial intelligence for planning, assembly, and manipulation.

Fall 2020: COMS W4733 |
|||||

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

COMS 4733 | 001/10077 | T Th 4:10pm - 5:25pm 833 Seeley W. Mudd Building |
Shuran Song | 3 | 80/80 |

**COMS W4735 Visual Interfaces to Computers.** *3 points*.

Lect: 3.

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*.

CC/GS: Partial Fulfillment of Science Requirement

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 W4771 Machine Learning.** *3 points*.

Lect: 3.

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.

Fall 2020: COMS W4771 |
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|

COMS 4771 | 001/10078 | T Th 1:10pm - 3:40pm Online Only |
Nakul Verma | 3 | 0/110 |

COMS 4771 | 002/10079 | T Th 1:10pm - 3:40pm 203 Mathematics Building |
Daniel Hsu | 3 | 75/110 |

COMS 4771 | R02/22807 | F 10:10am - 12:00pm 301 Pupin Laboratories |
Daniel Hsu | 3 | 0/110 |

COMS 4771 | V01/21924 | |
Nakul Verma | 3 | 0/99 |

**COMS W4772 Advanced Machine Learning.** *3 points*.

Lect: 3.

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.

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 data structures for fast Nearest Neighbor search such as Cover Trees and LSH. Algorithms will be implemented in either Matlab or Python.

**COMS W4774 Unsupervised Learning.** *3 points*.

Prerequisites: Solid background in multivariate calculus, linear algebra, basic probability, and algorithms.

Prerequisites: see notes re: 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.

Fall 2020: COMS W4774 |
|||||

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

COMS 4774 | 001/21884 | T Th 1:10pm - 3:40pm Online Only |
Nakul Verma | 3 | 0/60 |

**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

Fall 2020: COMS W4775 |
|||||

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

COMS 4775 | 001/21899 | M W 4:10pm - 5:25pm 717 Hamilton Hall |
Elias Bareinboim | 3.00 | 28/40 |

**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*.

Lect.: 3

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 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 point*.

Prerequisites: obtained internship and approval from faculty advisor.

Only for M.S. students in the Computer Science department who need relevant work experience as part of their program of study. Final report required. This course may not be taken for pass/fail credit or audited.

**COMS W4995 Special topics in computer science, I.** *3 points*.

Lect: 3.

Prerequisites: Instructor's permission.

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.

Fall 2020: COMS W4995 |
|||||

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

COMS 4995 | 001/10081 | T 4:10pm - 6:40pm 227 Seeley W. Mudd Building |
Paul Blaer | 3 | 12/30 |

COMS 4995 | 003/10082 | M W 5:40pm - 6:55pm Online Only |
Stephen Edwards | 3 | 58/80 |

COMS 4995 | 004/10850 | T Th 2:40pm - 3:55pm Online Only |
Peter Belhumeur | 3 | 58/60 |

COMS 4995 | 006/14067 | Th 6:10pm - 8:00pm 402 Chandler |
Tristan Boutros | 3 | 50/60 |

COMS 4995 | 008/21412 | M 7:00pm - 9:30pm 833 Seeley W. Mudd Building |
Bryan Gibson | 3 | 48/120 |

COMS 4995 | 009/21413 | Th 7:00pm - 9:30pm 501 Schermerhorn Hall |
Joshua Gordon | 3 | 113/200 |

COMS 4995 | 010/22251 | T Th 5:40pm - 6:55pm 413 Kent Hall |
Timothy Paine | 3 | 31/65 |

COMS 4995 | V03/21556 | |
Stephen Edwards | 3 | 0/99 |

COMS 4995 | V09/21959 | |
Joshua Gordon | 3 | 14/99 |

**COMS W4996 Special topics in computer science, II.** *3 points*.

Lect: 3.**Not offered during 2020-21 academic year.**

Prerequisites: Instructor's permission.

A continuation of COMS W4995 when the special topic extends over two terms.

## Computer Science - English

## Computer Science - Electrical Engineering

**CSEE W3827 Fundamentals of Computer Systems.** *3 points*.

Lect: 3.

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.

Fall 2020: CSEE W3827 |
|||||

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

CSEE 3827 | 001/10806 | T Th 10:10am - 11:25am Online Only |
Martha Kim | 3 | 162/180 |

CSEE 3827 | 002/10807 | T Th 11:40am - 12:55pm Online Only |
Martha Kim | 3 | 166/180 |

**CSEE W4119 COMPUTER NETWORKS.** *3.00 points*.

Lect: 3.

Prerequisites: Comfort with basic probability. Programming fluency in Python, C++, Java, or Ruby (please see section course page for specific language requirements).

Corequisites: IEOR E3658

Prerequisites: Comfort with basic probability. Programming fluency in Python, C , Java, or Ruby (please see section course page for specific language requirements). 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

Fall 2020: CSEE W4119 |
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|

CSEE 4119 | 001/13939 | T Th 2:40pm - 3:55pm Online Only |
Ethan Katz-Bassett | 3.00 | 76/160 |

CSEE 4119 | 002/21498 | |
Gil Zussman | 3.00 | 19/80 |

**CSEE W4121 COMPUTER SYSTEMS FOR DATA SCIENCE.** *3 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.

**CSEE W4140 Networking Laboratory.** *3 points*.

Lect: 3.

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*.

Lect: 3.

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.

Fall 2020: CSEE W4823 |
|||||

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

CSEE 4823 | 001/10727 | T Th 2:40pm - 3:55pm Online Only |
Mingoo Seok | 3 | 32/80 |

**CSEE W4824 Computer Architecture.** *3 points*.

Lect: 3.

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.

Fall 2020: CSEE W4824 |
|||||

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

CSEE 4824 | 001/10811 | M W 2:40pm - 3:55pm Online Only |
Simha Sethumadhavan | 3 | 64/70 |

CSEE 4824 | V01/21557 | |
Simha Sethumadhavan | 3 | 3/99 |

**CSEE W4840 Embedded Systems.** *3 points*.

Lect: 3.

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.

**CSEE W4868 System-on-chip platforms.** *3 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.

Fall 2020: CSEE W4868 |
|||||

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

CSEE 4868 | 001/11670 | T Th 11:40am - 12:55pm 717 Hamilton Hall |
Luca Carloni | 3 | 33/60 |

## Computer Science - Biomedical Engineering

**CBMF W4761 Computational Genomics.** *3 points*.

Lect: 3.

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.

Fall 2020: CBMF W4761 |
|||||

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

CBMF 4761 | 001/21883 | M W 6:40pm - 7:55pm 834 Seeley W. Mudd Building |
Itshack Pe'er | 3 | 16/40 |