Approved UMass Amherst Courses Outside of Computer Science
Pre-approved courses count toward the MS, MS/Phd, and PhD requirements, subject to any overall restrictions.
The courses below have been pre-approved to count toward the MS, MS/PhD, and PhD requirements, subject to any overall restrictions.
Note: Any course not on this pre-approved list not count towards the MS degree. Exceptions may be granted, provided they are requested well before the end of the add/drop period and explicitly approved by the MS program director. Exception requests are reviewed on a case-by-case basis and are not guaranteed to be approved. In order to request an exception, please do the following:
- Send an email to the MS program director at mpd [at] cs [dot] umass [dot] edu (mpd[at]cs[dot]umass[dot]edu) and cc: Eileen Hamel, Associate Director of Graduate Programs (hamel [at] umass [dot] edu (hamel[at]umass[dot]edu))
- The subject line of the email should read "Outside Course Approval for..."
- The body of the email should include a detailed syllabus and weekly schedule of the course as well as a description of the number and nature (e.g., programming or otherwise) of assignments and projects.
Biostatistics
BIOSTAT 690B: Intro to Causal Inference
BIOSTAT 690JQ: Biostatistics Methods 3: Modern Applied
BIOSTAT 690NR: Biostatistics Methods 2: Applied Linear
BIOSTAT 690T: Applied Statistical Genetics
BIOSTAT 730: Applied Bayesian Statistical Modeling
BIOSTAT 740: Mixed Models and Analysis of Longitudinal Data
BIOSTAT 748: Applied Survival Analysis
BIOSTAT 749: Statistical Methods for Clinical Trials
BIOSTAT 790A: Causal Inference: special topics
Civil & Environmental Engineering
CEE 790STA- Advanced Probabilistic Machine Learning ***
CEE 590STA- Machine Learning Foundations and Applications
***This class may not be used toward the MS degree if COMPSCI 688 and COMPSCI 689 are also being counted toward the MS degree. It may be used if only one of the aforementioned courses is used.
DACSS
DACSS 601: Data Science Fundamentals
DACSS 602: Research Design
DACSS 603: Introduction to Quantitative Analysis
DACSS 695SL: Social Life of Algorithms
DACSS 756- Machine Learning for Social Sciences
DACSS 758- Text as Data
Courses not approved: DACSS 695C - Seminar Corporate Lobbying and the Global Economy; DACSS 690M - Math for Applied Data Science; DACSS 690A - Data Engineering
Economics
ECON 701: Microeconomic Theory
Electrical and Computer Engineering
ECE 547: Security Engineering
ECE 556: Introduction to Cryptography
ECE 565: Digital Signal Processing
ECE 568: Computer Architecture
ECE 590C- Quantum Computing for Communication Networks
ECE 597: Math Tools for Data Science
ECE 597LS: Hardware Design for Machine Learning Systems
ECE 603: Probability and Random Processes
ECE 606: Electromagnetic Field Theory
ECE 608: Signal Theory
ECE 634: Optimal Control of Dynamic Systems
ECE 656: Introduction to Cryptography
ECE 671: Computer Networks
ECE 674: Green Computing
ECE 697A: Advanced Computer Networks and Wireless Systems
ECE 697BE- Introduction to Biosensors and Bioelectronics
ECE 697CS: Introduction to Compressive Sensing
ECE 697LP: Design Principles for Low-Power Embedded Computer Systems
ECE 697LS: Hardware Design for Machine Learning
ECE 697SN: Online Social Networks
ECE 735: Stochastic Control Dynamic Systems
ECE 745: Advanced Communication Theory
ECE 746: Statistical Signal Processing
Information Security
INFOSEC 690F: Fraud Detection
INFOSEC 690R: Information Risk Management
INFOSEC 690S: System Defense and Test*
*This class is a computer science class as of Fall 2020; therefore, if the class was taken as CS 590A Systems Defense and Test, it is counted as a computer science class.
Linguistics
LINGUIST 509: Introduction to Computational Linguistics
LINGUIST 510: Introduction to Semantics
LINGUIST 603- Generative Phonology
LINGUIST 606- Phonological Theory
LINGUIST 610: Semantics and Generative Grammar
LINGUIST 692B: Formal Foundations of Linguistic Theory
LINGUIST 692C: Cognitive Modeling
Mathematics and Statistics
MATH 513: Combinatorics*
MATH 532: Topics in Ordinary Differential Equations
MATH 535: Statistical Computing
MATH 545: Linear Algebra for Applied Mathematics
MATH 551: Scientific Computing
MATH 557: Linear Optimization and Polytopes
MATH 571: Introduction to Mathematical Cryptography
MATH 590STA: Introduction to Mathematical Machine Learning
MATH 597U: Introduction to Stochastic Processes and Applications
MATH 605: Probability Theory
MATH 611: Algebra I
MATH 612: Algebra II
MATH 623: Real Analysis I
MATH 624: Real Analysis II
MATH 651: Numerical Analysis I
MATH 652: Numerical Solution of PDEs
Math 655: Biomed and Health Data Analysis
MATH 671: Topology
MATH 697CM: ST-Combinatorial Optimization
MATH 697PA: ST–Math Foundations/Probabilistic AI
MATH 697FA: ST–Math Foundations/Probabilistic AI 2
MATH 697U: Stochastic Processes and Applications
MATH 706: Stochastic Calculus
MATH 717: Representation Theory
STAT 501: Methods of Applied Statistics
STAT 511: Multivariate Statistical Methods
STAT 525: Regression Analysis
STAT 535: Statistical Computing
STAT 597BD/Math 655: Biomed and Health Data Analysis
STAT 607: Mathematical Statistics I
STAT 608: Mathematical Statistics II
STAT 610: Bayesian Statistics
STAT 625: Regression Modeling
STAT 690STA: Applied Semiparametric Regression
STAT 697ML: Statistical Machine Learning
STAT 697TS: Time Series Analysis and Applications
STAT 697U Stochastic Processes and Applications
STAT 708: Applied Stochastic Models and Methods
Courses not approved: STAT 506, 515, and 516
*Match 513 is cross-listed with COMPSCI 575
Mechanical and Industrial Engineering
MIE 532: Network Optimization
MIE 620: Linear Programming
MIE 670: Technical Project Management
MIE 684: Stochastic Processes in Industrial Engineering I
MIE 697U: Strategy-Driven Engineering Innovation
MIE 724: Nonlinear and Dynamic Programming
Courses not approved: MIE 671- Product Management
Physics
Physics 564: Advanced Quantum Mechanics
Physics 601: Classical Mechanics
Physics 605: Methods Math Physics
Physics 614: Quantum Mechanics I
Physics 615: Quantum Mechanics II
School of Management
SCH-MGMT 597: FA–Foundations of Accounting
SCH-MGMT 602: Business Intelligence and Analytics
SCH-MGMT 644: Economic Analysis for Manager
SCH-MGMT 650: Statistics for Business
SCH-MGMT 680: Leadership and Organizational Behavior
SCH-MGMT 697DM: Web Analytics for Digital Marketing
SCH-MGMT 697RT: Artificial Intelligence for Business
Courses not approved: SCH-MGMT 597FF, 797FF, 797 VL ST, 697CV, 660, 609, 821 & 822