Fall 2021 Graduate Course Instruction Modes and Registration Information

The Courant Computer Science department designed our fall 2021 offerings, following university and GSAS guidance, and state and city health and safety guidelines. Each section received an instruction mode designation.

  • Online: Faculty and all students are remote; there is no physical classroom.
  • Blended: The section or an associated activity (tutorials or project sessions) are partially in-person with rotation of in-person and remote attendance.
  • In-Person: The section is in-person with ordinary meetings.

International students with certain visa restrictions will have an option to attend some classes remotely.

A list of graduate-level courses for each mode can be found below. This list is up-to-date as of May 19, 2021. Course designations may be revised based on the guidance we get from the university. We will inform all registered students promptly if a course designation changes.

For some courses, the in-person component structure and scheduling is not finalized yet; additional information will be posted on the course web pages and in Albert.

BLENDED

The instruction mode for the following courses is blended lecture unless noted otherwise.

  • CSCI-GA.1170 Fundamental Algorithms
    • CSCI-GA.1170-001 Fundamental Algorithms (lecture online)
      • CSCI-GA.1170-002 Fundamental Algorithms Recitation (in-person)
      • CSCI-GA.1170-005 Fundamental Algorithms Recitation (online)
    • CSCI-GA.1170-003 Fundamental Algorithms (lecture online)
      • CSCI-GA.1170-004 Fundamental Algorithms Recitation (online)
      • CSCI-GA.1170-007 Fundamental Algorithms Recitation (in-person)
  • CSCI-GA.2110 Programming Languages
    • CSCI-GA.2110-001 Programming Languages (lecture in-person)
      • CSCI-GA.2110-002 Programming Languages Recitation (in-person)
      • CSCI-GA.2110-006 Programming Languages Recitation (online)
    • CSCI-GA.2110-003 Programming Languages (lecture online)
      • CSCI-GA.2110-007 Programming Languages Recitation (blended)
  • CSCI-GA.2250-001 Operating Systems
  • CSCI-GA.2250-003 Operating Systems
  • CSCI-GA.2434-001 Advanced Database Systems
  • CSCI-GA.3033-085 Special Topics: Cloud and Machine Learning

ONLINE

  • CSCI-GA.1180-001 Mathematical Techniques for CS Applications
  • CSCI-GA.2433-001 Database Systems
  • CSCI-GA.2433-002 Database Systems
  • CSCI-GA.3033-084 Special Topics: High Performance Machine Learning

IN-PERSON

  • CSCI-GA.1133-001 PAC I
    • CSCI-GA.1133-002 PAC I Recitation
  • CSCI-GA.2112-001 Scientific Computing
  • CSCI-GA.2250-002 Operating Systems
  • CSCI-GA.2262-001 Data Communications and Networks
  • CSCI-GA.2270-001 Computer Graphics
  • CSCI-GA.2271-001 Computer Vision
  • CSCI-GA.2420-001 Numerical Methods I
  • CSCI-GA.2436-001 Realtime and Big Data Analytics
  • CSCI-GA.2560-001 Artificial Intelligence
  • CSCI-GA.2566-001 Foundations of Machine Learning
  • CSCI-GA.2590-001 Natural Language Processing
  • CSCI-GA.2621-001 Distributed Systems
  • CSCI-GA.2630-001 Foundations of Networks and Mobile Systems (MS-CEI only)
    • CSCI-GA.2630-002 Foundations of Networks and Mobile Systems Lab (MS-CEI only)
  • CSCI-GA.2810-001 Design and Innovation (MS-CEI only)
    • CSCI-GA.2810-002 Design and Innovation Lab (MS-CEI only)
  • CSCI-GA.2820-001 DevOps and Agile Methodologies
    • CSCI-GA.2820-002 DevOps and Agile Methodologies Lab
  • CSCI-GA.2945-002 Adv Topics Num Analysis: Numerical Optimization
  • CSCI-GA.2965-001 Heuristic Problem Solving
  • CSCI-GA.3033-025 Special Topics: Graphics Processing Units (GPUs): Architecture & Programming
  • CSCI-GA.3033-034 Special Topics: Multicore Processors: Architecture & Programming
  • CSCI-GA.3033-061 Special Topics: Predictive Analytics
  • CSCI-GA.3033-083 Special Topics in Data Science: Machine Learning for Healthcare
    • CSCI-GA.3033-183 Special Topics in Data Science: Machine Learning for Healthcare Lab
  • CSCI-GA.3033-090 Special Topics: Deep Reinforcement Learning
  • CSCI-GA.3033-093 Special Topics: Introduction to Deep Learning Systems
  • CSCI-GA.3110-001 Honors Programming Languages
  • CSCI-GA.3205-001 Applied Cryptography & Network Security
  • CSCI-GA.3520-001 Honors Analysis of Algorithms
  • CSCI-GA.3812-001 Information Technology Projects
  • CSCI-GA.3840-001 Master’s Thesis Research
  • CSCI-GA.3850-001 PhD Seminar: Cryptography
  • CSCI-GA.3850-004 PhD Seminar: Formal Methods
  • CSCI-GA.3860-001 PhD Thesis Research

GRADUATE COURSES OFFERED IN SHANGHAI

In light of the US travel restrictions due to the COVID-19 pandemic, Courant Computer Science department expects to offer the following NYU graduate computer science classes this spring in Shanghai at the NYU-Shanghai campus.

  • CSCI-GA.2433-011 Database Systems
    • Instructor: Xiaoyang Sean Wang
  • CSCI-GA.2440-011 Software Engineering
    • Instructor: Lihua Xu

Additional information on course offerings at NYUSH will be posted on this site once confirmed.

You can register for these classes directly in Albert. These classes will be held in person, and will have the same content and fulfill the same requirements as the corresponding courses at NYU-New York. These classes will commence the week of August 30, 2021.

Additionally, Courant Computer Science will offer courses jointly with the NYU Tandon School of Engineering in Shanghai. For MSCS students, these classes would count towards the 21 credits of standard graduate CS classroom-based courses. Additional information on course offerings at NYUSH will be posted on this site once confirmed.

  • CSCI-GA.3033-117/CS-GY 6033-SHAN Design and Analysis of Algorithms I
    • Instructor: Manuel Charlemagne
  • CSCI-GA.3033-256/CS-GY 6923-SHAN Machine Learning
    • Instructor: Li Guo

INTERNATIONAL GRADUATE STUDENTS: MEETING IN-PERSON REQUIREMENTS

Update 05/05/2021: All international students who are newly enrolled as of Fall 2021 and hope to gain entry to the US for that term should be registered for at least one course during the semester that is not online. Acceptable courses are those whose instructional mode is listed in Albert as "In-Person," "Blended," or "Independent Studies." Essentially, whatever term the student starts in the US cannot be fully online. Please contact the Office of Global Services (OGS) for international students for further guidance.