Computer Science MS

1 Years On Campus Mba Program

Brandeis University

Program Overview

The Master of Science in Computer Science (MS) at Brandeis University is designed for students who want to strengthen their technical expertise and pursue advanced careers in software engineering, artificial intelligence, robotics, and other computing fields. The program offers two pathways: a nine-course, three-semester track for students with a computer science background and a 12-course, four-semester track for students from other academic disciplines, combining foundational computing knowledge with advanced coursework and specialized training.

Curriculum Structure

Foundation Coursework (MS4 Track): Students without a previous computer science degree begin by developing essential programming and computational knowledge through COSI 12b: Advanced Programming Techniques, COSI 21a: Data Structures and Algorithms, and COSI 29a: Discrete Structures. These courses establish the foundations required to progress into advanced computer science subjects and prepare students for more specialized technical learning.

Advanced Computer Science Coursework (MS3 and MS4 Tracks): Students complete graduate-level electives covering areas such as distributed computing, big data, machine learning, computational linguistics, artificial intelligence, and software development. Courses such as COSI 131a: Operating Systems, along with approved courses in systems, theory, and artificial intelligence, help students develop advanced programming, algorithmic, and software engineering capabilities.

Specialization and Independent Study: Students select electives according to their academic interests and career objectives, with opportunities to explore research-oriented subjects and interdisciplinary computing applications. They may also undertake COSI 210a: Independent Study, allowing them to work on faculty-supervised research or specialized projects.

Focus Areas

Artificial Intelligence, Machine Learning, Distributed Computing, Big Data, Computational Linguistics, Software Engineering, Programming Languages, Algorithms, Computer Systems, Operating Systems, Robotics, Bioinformatics, Information Theory, Parallel Computing.

Learning Outcomes

Graduates develop advanced programming and software engineering skills required to design and build large-scale applications and web-based systems. They gain graduate-level knowledge across at least two major areas of computer science, including systems, artificial intelligence and applied interdisciplinary computing, and theory. They also develop the ability to solve complex computing problems, apply ethical and professional practices, and prepare for advanced technical careers or doctoral studies.

Professional Alignment (Accreditation)

The program emphasizes practical software development, advanced computing concepts, and interdisciplinary research through its graduate coursework and independent study opportunities. Students benefit from Brandeis University's location near Boston and Cambridge, providing access to a strong technology ecosystem, industry networking events, career fairs, and professional development resources. No separate professional accreditation is specified for this master's program on the official university website.

Reputation (Employability Rankings)

Brandeis University's Michtom School of Computer Science provides students with opportunities to connect academic learning with the technology industry through networking events, recruiting visits, and career development support. The university identifies employers of its computer science graduates, including Google, Amazon, Microsoft, Bloomberg, Akamai, Blizzard Entertainment, Uber, and Dell EMC. Graduates have pursued careers as software developers, design engineers, robotics programmers, and researchers, while others have continued into doctoral studies.

Experiential Learning (Research, Projects, Internships etc.)

At Brandeis University, the Computer Science MS program is designed to provide students with a robust blend of theoretical knowledge and practical skills. Through hands-on experiences, students engage in real-world projects that prepare them for the dynamic tech landscape. The program emphasizes experiential learning, allowing students to apply their classroom knowledge in various settings, from collaborative group projects to internships with industry partners.

Brandeis offers state-of-the-art facilities and resources that enhance the learning experience, including:

- Research Labs: Access to specialized labs such as the Brandeis University Computational Neuroscience Lab and the Brandeis University Data Science Lab, where students can work on cutting-edge research projects.
- Internship Opportunities: Strong connections with local tech companies and organizations provide students with internship placements that offer invaluable industry experience.
- Collaborative Projects: Students often work in teams on projects that simulate real-world challenges, fostering teamwork and problem-solving skills.
- Software and Tools: Familiarity with industry-standard software and tools, including Python, R, and various machine learning frameworks, is integrated into the curriculum.
- Field Trips: Opportunities to visit tech companies and attend industry conferences, allowing students to network and gain insights into the latest trends and technologies.
- Libraries and Resources: Access to the Brandeis library system, which includes extensive digital resources and databases relevant to computer science research.
- Institutes and Centers: Collaboration with the Brandeis Institute for Data Science and the Brandeis Center for Computational Neuroscience, providing additional research and learning opportunities.

Progression & Future Opportunities

Brandeis University’s Master of Science in Computer Science program equips graduates with the skills and knowledge needed to excel in a rapidly evolving tech landscape. Alumni have successfully transitioned into roles such as Software Engineer, Data Scientist, and Cybersecurity Analyst, showcasing the program's strong emphasis on practical skills and industry relevance. Here’s what you can expect in terms of progression and future opportunities:

- University Services: Brandeis offers dedicated career services, including resume workshops, interview preparation, and networking events with industry professionals, ensuring you are well-prepared for the job market.
- Employment Stats and Salary Figures: Graduates from the Computer Science MS program have a high employment rate, with many securing positions within six months of graduation. The average starting salary for alumni is competitive, often exceeding $90,000 annually.
- University–Industry Partnerships: Brandeis has established partnerships with leading tech companies, providing students with internship opportunities and real-world projects that enhance learning and employability.
- Long-term Accreditation Value: The program is accredited and recognized for its rigorous curriculum, which not only prepares you for immediate employment but also holds value in the long term as the tech industry continues to evolve.
- Graduation Outcomes: The program boasts a strong track record of graduates who go on to work at top firms, including Google, Amazon, and Microsoft, reflecting the high demand for Brandeis alumni in the tech sector.

Further Academic Progression: After completing your MS in Computer Science, you may choose to pursue a Ph.D. in Computer Science or related fields, allowing you to delve deeper into research and potentially teach at the university level. Additionally, you could explore specialized certifications or professional development courses to enhance your expertise in areas such as artificial intelligence, machine learning, or data analytics. This pathway not only broadens your knowledge but also opens doors to advanced career opportunities in academia and industry.