Non-CS courses that may be applied to the CS credit requirements

There are two categories of courses without CS department course numbers ( that may be applied toward CS credit requirements. The first group (special cross-listed courses) may be counted anywhere that CS courses at the same level may be counted for the BS, BA, or minor. The second, larger group of courses may only count as lower-level elective credit for the BS degree.

Group 1 – Non-departmental, count as if they were CS

These special cross-listed courses are taught by joint faculty and/or used to have CS course numbers. As such, they may count towards your CS upper-level credits:

  • AS.050.375/675 Probabilistic Models of the Visual Cortex (Yuille)
  • EN.520.666 Information Extraction (Khudanpur)
  • EN.580.488/688 Foundations of Computational Biology & Bioinformatics II (Karchin)
  • EN.580.458 Computing the Transcriptome (Pertea)
  • EN.580.745 Mathematics of Deep Learning (Vidal)
  • EN.650.624 Network Security

Group 2 – CS “other” courses

A maximum of six total credits from the following courses may count toward the CS credit requirements for the BS in computer science.

They may be counted only as CS “other” credits, not CS upper-level credits, regardless of the course number. Note that not all cross-listed courses count for CS “other” credit—please look for the “CSCI-OTHR POS” tag. All course selections must be made with the explicit approval of your advisor. If you think a course should be added to this listing, please contact the CS Director of Undergraduate Studies and include a full syllabus with your request.

  • The following Electrical and Computer Engineering courses:
    • EN 520.216 Intro to VLSI
    • EN.520.349 Microprocessor Lab
    • EN.520.372 Programmable Device Lab
    • EN.520.385 Signals, Systems, and Learning (added 3/13/2020)
    • EN.520.412/612 Machine Learning for Signal Processing [as Analysis] (added 1/26/2018)
    • EN.520.414 Image Processing and Analysis (added 5/26/20)
    • EN.520.424 FPGA Synthesis Lab
    • EN.520.432 Medical Imaging Systems
    • EN.520.433 Medical Image Analysis
    • EN.520.439 Machine Learning for Medical Applications (added 11/28/22)
    • EN.520.447 Information Theory
    • EN.520.448 MSE Design Team Leader (Electronic Design Theory)
    • EN.520.450 Advanced Microprocessor Lab
    • EN.520.462/463 Leading Innovation Design Team (added 2/3/2021)
    • EN.520.491 CAD Design of Digital VLSI Systems I
  • The following Applied Math and Statistics courses (may count as CS “other” or for CS math requirement, but not both):
    • EN.553.287 Python for Data Science Applications (added 2019, “at most 4 S/U credits” restriction applies, too)
    • EN.553.361 (EN.550.361) Intro to Optimization
    • EN.553.362 (EN.550.362) Optimization II (added 12/2/2016)
    • EN.553.371 (EN.550.371) Cryptology and Coding
    • EN.553.402 Research and Design in Applied Mathematics: Data Mining (added 2/5/2019)
    • EN.553.436 (EN.550.436) Intro to Data Science (formerly Data Mining)
    • EN.553.450 Computational Molecular Medicine (added 3/2/2021)
    • EN.553.463 Network Models in Operations Research (added 12/11/2020)
    • EN.553.467 Deep Learning in Discrete Optimization (added 12/13/2018)
    • EN.553.471 (EN.550.471) Combinatorial Analysis
    • EN.553.472 (EN.550.472) Graph Theory
    • EN.553.493 Mathematical Image Analysis (added 2/7/2019)
  • The following Information Security Institute courses:
    • EN.650.631 (EN.650.431) Ethical Hacking
    • EN.650.656 (EN.650.457) Computer Forensics
    • EN.650.660 (EN.650.460) Software Vulnerability Analysis
    • EN.650 663 (EN.650.461) Cloud Computing Security
    • EN.650.654 Computer Intrusion Detection
    • EN.650.757 (EN.650.657) Advanced Computer Forensics
  • The following Biomedical Engineering courses:
    • EN.580.230 Intro to Genomic Data Analysis
    • EN.580.437 Biomedical Data Design (formerly Neuro Data Design I) (counts for oral as of 2017)
    • EN.580.438 Neuro Data Design II (counts for oral as of 2017)
    • EN.580.475 Biomedical Data Science (added 9/12/2019)
    • EN.580.477 Biomedical Data Science Lab (added 5/26/20)
    • EN.580.481 Precision Care Medicine (2nd semester only, added 10/30/2018)
    • EN.580.491 Learning Theory (added 12/2/16)
  • Miscellaneous courses:
    • AS.171.205 Introduction to Practical Data Science: Beautiful Data
    • AS.110.445 Mathematical and Computational Foundations of Data Science (added 11/28/2022)
    • AS.171.402 Applied Quantum Information (added 1/28/2022)
    • AS.250.302 Modeling Living Cell (added 3/16/18)
    • EN.660.345 Multidisciplinary Engineering Design I (Formerly EN.500.308) (added 9/1/2020)
    • EN.500.309 Multidisciplinary Engineering Design II (Formerly Advanced Multidisciplinary Design) (added 9/1/2020)
    • EN.500.115 Gateway Data Science (added 1/28/2022)
    • EN.540.414 Computational Protein Structure Prediction and Design (added 1/28/2022)
    • EN.660.410 Computer Science Innovation and Entrepreneurship (added fall 2021)

The following courses have already been rejected from inclusion on this list:

  • Bootcamp courses (EN.500.132/133/134) can only count as a substitute for Gateway Computing/AP credits and cannot be used for CS “other” credit.
  • A number of lower-level ECE courses, such as Intro ECE, DSF, Signals, Computational Modeling for ECE, etc.
  • Policy- and health-related ISI courses.
  • AS.080.321 Computational Neuroscience
  • AS.250.205 Introduction to Computing
  • AS.250.313 Molecular & Cellular Systems Biology
  • AS.250.353 Computational Biology
  • EN.553.335 Mathematics for a Better World
  • EN.580.485/487 Computational Medicine: Cardiology
  • EN.660.347 Multi-Disciplinary Action Lab