Courses

Course Offering Plan 

Course Offering Plan
Offering Plan Exceptions - Academic Year 2025-26 

Spring 2026

Spring 2026 - Overrides

Process for students who require special permission to enroll in university-scheduled CICS, COMPSCI, and INFO courses. 

Override Information »

Courses Not Yet on SPIRE - Spring 2026

The following NEW (or Revised) experimental courses are being reviewed by the Faculty Senate and will not appear on SPIRE until fully approved:

  • COMPSCI 490PF* Performance Engineering

    Instructor(s):  Emery Berger
    
Credits:  3  
    This course provides a systematic treatment of performance engineering—the analysis, measurement, and optimization of software systems. It covers how performance emerges from the interaction between algorithms, programming languages, compilers, operating systems, and modern hardware. Topics include algorithmic complexity, caching and memory hierarchies, concurrency and synchronization, vectorization, compiler and runtime optimizations, and profiling techniques for both CPU and GPU/accelerator execution. Students will conduct detailed performance studies, apply advanced profiling tools, and design and evaluate optimizations for real systems. The course emphasizes quantitative reasoning, experimental rigor, and clear performance reporting. This course counts as a CS Elective for the CS Major (BA or BS).

    Course URL:  not yet provided

    Prerequisites:  See Class Notes

    Eligibility:  JUNIOR AND SENIOR CS MAJORS ONLY.

    Class Notes:  MEETS WITH COMPSCI 690PF.  INSTRUCTOR CONSENT REQUIRED.  JUNIOR AND SENIOR CS MAJORS WITH GRADES OF AT LEAST A- IN BOTH COMPSCI 230 AND 377 ARE THE LEVEL OF BACKGROUND IN SYSTEMS THAT IS EXPECTED.  PAST DOCUMENTED EXPERIENCE WITH GITHUB PROJECTS STRONGLY PREFERRED.  THIS COURSE IS PROJECT- AND EXPERIMENT-INTENSIVE.  STUDENTS WILL ANALYZE REAL SOFTWARE SYSTEMS, PERFORM QUANTITATIVE PERFORMANCE MEASUREMENTS, AND REPORT RESULTS USING PROFESSIONAL STANDARDS.  FAMILIARITY WITH BOTH C/C++ AND PYTHON IS EXPECTED.  UNDERGRADUATE AND GRADUATE SECTIONS MEET TOGETHER BUT HAVE DISTINCT PROJECT EXPECTATIONS AND GRADING CRITERIA.  ENROLLMENT IS CAPPED TO SUPPORT IN-DEPTH MENTORING AND EVALUATION.

    Meeting Days/Times:  MW 4:00-5:15 PM

    *alpha subject to change

     
  • COMPSCI 590RM* Research Methods for Empirical Computer Science
    
Instructor(s):  David Jensen

    Credits:  3

    This course introduces concepts, practices, and tools for conducting effective research. You will learn how to read technical papers, interpret published research, assess the research frontier, select research topics, devise research questions and hypotheses, propose and plan research activities, analyze experimental results, and report those results. The course is structured around four activities: (1) Synchronous and asynchronous lectures on basic research strategies and techniques; (2) Synchronous activities that apply course concepts; (3) Reading and discussions of technical papers in computer science; and (4) An individual semester-long project that replicates an existing published study in computer science. The course requires significant reading, reviewing, and writing. Students are expected to participate actively in class activities. The course is intended for MS and advanced undergraduate students. It provides a grounding in research methods that will aid your entry into research-oriented industrial positions and PhD studies. For undergraduates considering graduate studies, this course will help inform and accelerate that direction. For undergraduates, this course can be used to satisfy the 499Y requirement for Departmental and Multidisciplinary Honors students whose theses or projects have a substantial empirical component.

    Course URL:  https://groups.cs.umass.edu/jensen/teaching/research-methods/

    Prerequisites:  See Class Notes

    Eligibility:  
UNIV LEC 01:  JUNIOR AND SENIOR CS AND INFORM MAJORS IN COMMONWEALTH HONORS COLLEGE.
  UNIV LEC 02:  GRADUATE CMPSCI STUDENTS ONLY.

    Class Notes:  MEETS WITH COMPSCI 602.  DEPARTMENT CONSENT REQUIRED.  UNDERGRADUATE CHC CS AND INFORM MAJORS WITH HPD AND INSTRUCTOR PERMISSION.

    Meeting Days/Times:  TuTh 4:00-5:15 PM

    *alpha subject to change

     
  • COMPSCI 690AG* Algorithmic Game Theory
    
Instructor(s):  Hedyeh Beyhaghi
    
Credits:  3

    This course offers a graduate-level introduction to topics at the interface of theoretical computer science and economics, with a focus on strategic and learning-based interactions. We will cover the basics of mechanism design, auctions, and pricing, as well as models of strategic behavior such as Nash equilibrium and the price of anarchy. Additional topics include learning in games, strategic classification, and dynamics in multi-agent systems.

    Course URL:  not yet provided
    Eligibility:  CMPSCI GRADUATE STUDENTS ONLY.

    Class Notes:  BASIC BACKGROUND IN ALGORITHMS AND COMPLEXITY (COMPSCI 311 OR EQUIVALENT) AND PROBABILITY.  AS A COMPARISON, COMPSCI 515 FOCUSES ON COOPERATION, SOCIAL CHOICE, AND FAIR DIVISION.  THIS COURSE EMPHASIZES COMPETITIVE SETTINGS AND MECHANISM DESIGN.  STUDENTS INTERESTED IN BOTH PERSPECTIVES ARE ENCOURAGED TO TAKE BOTH COURSES, WHICH ARE DESIGNED TO BE COMPLEMENTARY.  PRIOR COMPLETION OF COMPSCI 515 IS NOT REQUIRED.  
    Meeting Days/Times:  MW 2:30-3:45 PM

    *alpha subject to change

     
  • COMPSCI 690PF* Performance Engineering

    Instructor(s):  Emery Berger

    Credits:  3

    This course provides a systematic treatment of performance engineering—the analysis, measurement, and optimization of software systems. It covers how performance emerges from the interaction between algorithms, programming languages, compilers, operating systems, and modern hardware. Topics include algorithmic complexity, caching and memory hierarchies, concurrency and synchronization, vectorization, compiler and runtime optimizations, and profiling techniques for both CPU and GPU/accelerator execution. Students will conduct detailed performance studies, apply advanced profiling tools, and design and evaluate optimizations for real systems. The course emphasizes quantitative reasoning, experimental rigor, and clear performance reporting.

    Course URL:  not yet provided
    
Eligibility:  CMPSCI GRADUATE STUDENTS ONLY.
    Class Notes:  MEETS WITH COMPSCI 490PF.  THIS COURSE IS PROJECT- AND EXPERIMENT-INTENSIVE.  STUDENTS WILL ANALYZE REAL SOFTWARE SYSTEMS, PERFORM QUANTITATIVE PERFORMANCE MEASUREMENTS, AND REPORT RESULTS USING PROFESSIONAL STANDARDS.  FAMILIARITY WITH BOTH C/C++ AND PYTHON IS EXPECTED.  ENROLLMENT IS CAPPED TO SUPPORT IN-DEPTH MENTORING AND EVALUATION.  BACKGROUND IN SYSTEMS PROGRAMMING, DATABASE IMPLEMENTATION, OR EQUIVALENT EXPERIENCE.  

    Meeting Days/Times:  MW 4:00-5:15 PM

    *alpha subject to change
     

The following courses are in the process of being added and will appear on SPIRE as soon as Course & Classroom Management has the opportunity to add the course:

  • Courses not requiring Faculty Senate approval will be listed here once submitted to Course & Classroom Management.

Winter 2026

Winter 2026 - Override Requests for CICS, COMPSCI, and INFO Courses

Process for students who require special permission to enroll in courses offered through University+ (formerly University Without Walls).

Override Information »

Fall 2025

Fall 2025 - Overrides

Process for students who require special permission to enroll in university-scheduled CICS, COMPSCI, and INFO courses. 

Override Information »

Summer 2025

Summer 2025 - Override Requests for CICS, COMPSCI, and INFO Courses

Process for students who require special permission to enroll in courses offered through University+ (formerly University Without Walls).

Override Information »

Spring 2025

Fall 2024

Other Helpful Tools 

Courses Outside the College 

Additional computer science-related courses are also offered in the Department of Electrical and Computer Engineering at UMass and at nearby Amherst, Hampshire, Mount Holyoke, and Smith Colleges. The Five College Course Catalog combines course schedule information from these colleges, as well as UMass.