MS Software Engineering, Specialization in Data Science
Advance your career with an MSSE, specialization in Data Science !
Our program prepares students and professionals to investigate and summarize real-world data of all sizes, ask the right questions, find informative answers, and create visualizations that effectively communicate their results. Through a combination of theory and practical data analyses, students learn the foundations of extracting knowledge from data, verifying the utility of the information, and scaling their analysis to Big Data. The program emphasizes teamwork throughout the curriculum, as an essential part of preparing students for working in industry.
This specialization prepares students to practice the entire analytics process, from translating real-world objects into data to presenting information gleaned from the analysis.
- PreQualify Now
Applications are open for Fall 2022
For domestic students: application deadline is May 1, 2022, document deadline is May 20, 2022.
For international students: application deadline is April 1, 2022, document deadline is April 20, 2022.
Admissions reviews and decisions for this program will begin in February. We will continue to admit students on a rolling bases through the month of June.
- Key Benefits
Outstanding Faculty: Industry leaders and academic experts offer a wide range of practical knowledge and experience in engineering and software development.
Location, Location, Location: All courses are offered in Silicon Valley near high-tech employers and easily accessible from anywhere in the San Francisco Bay Area. You can complete your degree while holding an internship and/or continuing your career!
Convenience: designed for working professionals who want to earn advanced degrees through accelerated programs.
Affordable Education: San Jose State University offers an outstanding educational value, and many local businesses will pay partial or full tuition for employees who enroll in graduate degree programs.
- Program and Course Descriptions
- Specialized Data Science Courses
CMPE 256 - Web and Big Data Mining
- Data mining and machine learning algorithms and applications for large amounts of data. Information retrieval and search engines, social network analysis, link analysis, and ranking. Web personalization, recommender systems, opinion mining and sentiment analysis, and advanced topics.
CMPE 257 - Machine Learning
- Machine learning concepts, feasibility and learning types, theory of generalization, bias and variance, linear models for classification and regression, nonlinear transformation, regularization and validation, kernel methods, radial basis functions, support vector machines, ensemble methods, neural networks, and hands-on projects.
CMPE 260 - Reinforcement Learning
- Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL). Topics include RL formalism, Markov decision process, Deep Q-Network, and reinforcement learning programming platforms. Also covered are relevant applications of RL in various fields.
- Program Descriptions
- Each course meets one night a week, for 16 weeks, following the SJSU academic calendar. Dependent on cohort path, courses may also meet on a few Saturdays.
- Classes are delivered year-round in fall, spring, and summer.
- There are 11 courses, for a total of 33 graduate-level units that fulfill the requirements for earning a Master of Science in Software Engineering degree.
- Students must satisfy the Graduate Writing Assessment Requirement.
- Class Location
3000 Mission College Blvd, Santa Clara, CA
- Program Learning Outcomes (PLOs)
For students graduating with MS Software Engineering degrees:
1. Be able to demonstrate an understanding of advanced knowledge of the practice of software engineering, from vision to analysis, design, validation and deployment.
2. Be able to tackle complex engineering problems and tasks, using contemporary engineering principles, methodologies and tools.
3. Be able to demonstrate leadership and the ability to participate in teamwork in an environment with different disciplines of engineering, science and business.
4. Be aware of ethical, economic and environmental implications of their work, as appropriate.
5. Be able to advance successfully in the engineering profession, and sustain a process of lifelong learning in engineering or other professional areas.
6. Be able to communicate effectively, in both oral and written forms.
Applying for admission to an off-campus cohort at San Jose State University is not a guarantee that the program will occur. Cohorts must meet minimum enrollment standards in order to take place. Please be aware that in the event a cohort does not launch due to low enrollment, any and all associated application fees cannot be refunded.