MSSE is an online professional masters program that prepares students for careers in computational science, data science, machine learning, and software engineering. The program is designed to train students with backgrounds in chemistry, physics, biology, computer science, or from other physical science disciplines. The MSSE provides students with the tools, software engineering practices, leadership, management, and entrepreneurial skills needed to create or lead science- or engineering-based enterprises. The 29-units of online coursework include a capstone project with an industrial or government lab partner.
The MSSE program is available both full-time and part-time. The part-time program is designed for working professionals or students with other responsibilities. Review the sample plans below.
The MSSE program is available with a fall start or a summer start. The summer start is recommended for those with less mastery in advanced math and programming, or for students who have been out of school for longer. If you have concerns about which start is right for you, dont hestiate to email us at msse@berkeley.edu or schedule a meeting with an admissions representative.
MSSE launches with an online two-week bootcamp on the foundations of programming and software engineering for students starting in Fall, and ends with a two-week on-campus* leadership bootcamp for all students. The two bootcamps in the program each are taught full-time even for part-time students, as they are intensive two week courses. *Students who are unable to travel to campus can talk to their advisor about online options.
Preview Program Schedules
Full-Time Summer Start
CHEM 272: Python for Molecular Science
CHEM 273: Numerical Methods for Computational Science
CHEM 274A: Programming Languages for Molecular Sciences: Python and C++
CHEM 274B : Software Engineering Fundamentals for Molecular Sciences
DATA 200S: Principles and Techniques of Data Science
CHEM 277B: Machine Learning Algorithms
CHEM 282A: Leadership Bootcamp
CHEM 282B: MSSE Leadership and Project Management
CHEM 281 : Software Engineering for Scientific Computing
CS 267 : Applications of Parallel Computing
or
CHEM 279: Numerical Algorithms applied to Computational Quantum Chemistry
CHEM 278: Ethics in Molecular Science and Software Engineering
CHEM 283 : Capstone Project
Full-Time Fall Start
CHEM 280: Foundations of Programming and Software Engineering for Molecular Sciences
CHEM 274A: Programming Languages for Molecular Sciences: Python and C++
CHEM 274B : Software Engineering Fundamentals for Molecular Sciences
DATA 200S: Principles and Techniques of Data Science
CHEM 277B: Machine Learning Algorithms
CHEM 282A: Leadership Bootcamp
CHEM 281 : Software Engineering for Scientific Computing
CHEM 278: Ethics in Molecular Science and Software Engineering
CHEM 279 : Numerical Algorithms Applied to Computational Chemistry
CS 267 : Applications of Parallel Computing
CHEM 283 : Capstone Project
Part-Time Summer Start
Part-time course schedules may vary. The Part-time program is intended for working professionals. During the semester, one unit is equivalent to 3 hours of work on average. Please email msse@berkeley.edu with any questions.
CHEM 272: Python for Molecular Science
CHEM 273: Numerical Methods for Computational Science
Year 1
CHEM 274A: Programming Languages for Molecular Sciences: Python and C++
CHEM 274B : Software Engineering Fundamentals for Molecular Sciences
DATA 200S: Principles and Techniques of Data Science
CHEM 281: Software Engineering for Scientific Computing
Year 2
CHEM 277B: Machine Learning Algorithms
CHEM 279: Numerical Algorithms applied to Computational Quantum Chemistry
CHEM 282A: Leadership Bootcamp
CHEM 278: Ethics in Molecular Science and Software Engineering
CHEM 282B: MSSE Leadership and Project Management
CHEM 283 : Capstone Project
Part-Time Fall Start
Part-time course schedules may vary. The Part-time program is intended for working professionals. During the semester, one unit is equivalent to 3 hours of work on average. Please email msse@berkeley.edu with any questions.
CHEM 280: Foundations of Programming and Software Engineering for Molecular Sciences
Year 1
CHEM 274A: Programming Languages for Molecular Sciences: Python and C++
CHEM 274B : Software Engineering Fundamentals for Molecular Sciences
DATA 200S: Principles and Techniques of Data Science
CHEM 281: Software Engineering for Scientific Computing
CHEM 278: Ethics in Molecular Science and Software Engineering
Year 2
CHEM 277B: Machine Learning Algorithms
CHEM 279: Numerical Algorithms applied to Computational Quantum Chemistry
CHEM 282A: Leadership Bootcamp
CS 267 : Applications of Parallel Computing
CHEM 282B: MSSE Leadership and Project Management
CHEM 283 : Capstone Project