Graduate Courses that count for Elective / Honors credit

No MPCS courses may be taken for credit towards your Bx degree

To enroll, you must print out and complete a consent form ad turn it in to the registrar. You may not enroll in graduate courses online.

CMSC 32200 - Computer Architecture
CMSC 32630 - Advanced Implementation of Computer Languages
CMSC 33100 - Advanced Operating Systems
CMSC 33210 - Usable Security
CMSC 33250 - Introduction to Computer Security - if you have not taken 232
CMSC 33251-1 - Topics in Computer Security: Data-Driven Security and Privacy
CMSC 33300 - Networks & Distributed Systems
CMSC 33301 - Computer Architecture for Machine Learning
CMSC 33400 - Mobile Computing
CMSC 33410 - Quantum Computing
CMSC 33520 - Data Intensive Systems
CMSC 33550 - Introduction to Databases - if you have not taken CMSC 23500
CMSC 33710 - Scientific Visualization - if you have not taken CMSC 23710
CMSC 33750 - Machine Learning and Cancer
CMSC 34702 - Mobile and IoT Systems
CMSC 35050 - Computational Linguistics
CMSC 35200 - Deep Learning
CMSC 35400 - Machine Learning - by special permission
CMSC 35470 - Convex Optimization
CMSC 37000 - Algorithms
CMSC 37110 - Discrete Mathematics
CMSC 38000 - Computability Theory I
CMSC 38400 - Cryptography
CMSC 38500 - Computability and Complexity Theory
CMSC 37800 - Computability Theory II
CMSC 38800 / Math 38800 - Complexity Theory
CMSC 37812 - Mathematical Computation III: Numerical Methods for PDEs
CMSC 38815 - Geometric Complexity
CMSC 39000 - Computational Geometry
CMSC 39010 - Computational and Metric Geometry
CMSC 39600 - Topics In Theoretical Computer Science: Fine-Grained Algorithms and Complexity
TTIC 31020 - Introduction to Statistical Machine Learning
TTIC 31050 - Introduction to Bioinformatics and Computational Biology
TTIC 31110 - Speech Technologies
TTIC 31180 - Probabilistic Graphical Methods
TTIC 31190 - Natural Language Processing
TTIC 31210 - Advanced Natural Language Processing
TTIC 31220 - Unsupervised Learning and Large-Scale Data Analysis
TTIC 31120 - Statistical and Computational Learning Theory
TTIC 31230 - Fundamentals of Deep Learning
TTIC 31250 - An Introduction to the Theory of Machine Learning