The USTSV Master of Computer Science and Engineering offers a graduate degree with the following four majors: Artificial Intelligence (AI), Data Science,Software Engineering and VLSI Design The MSCSE degree can be completed entirely with course work; however, an optional thesis is available for those students with an affinity for research.

A Graduate Certificate in several computer science related fields is available through Hacker Academy for engineers and students ready to develop the skills necessary to face the increasing technical challenges in today's high tech industry.

Succeed in today’s competitive, high tech environment with a Master of Science in Computer Science and Engineering from USTSV.

Designed to prepare students in the concepts and latest technologies of today’s hardware and software systems, USTSV’s computer science and engineering program provides the skills and knowledge necessary to become cutting edge engineers. The program prepares students for top tier software and hardware careers in the four major areas that have statistically high demand and placement rates in Silicon Valley.

USTSV takes advantage of our location in the heart of Silicon Valley, offering the best curriculum and latest advances in design, programming, and the application of today’s software and hardware systems. In this program, students are also taught vital leadership and entrepreneurial skills necessary to compete in today’s high-stakes job market.

MSCSE students are expected to enroll in one of the four major degree program offerings and complete real-client class projects and evaluation assignments each trimester.

Students will need to demonstrate their understanding of algorithms through research and creation, a mastery of operating systems, compilers, internals of databases, visual and sound recognition and robotics. To prepare for future advancement in technology, students are armed with theoretical knowledge and the ability to contribute to computerization in fields not yet discovered.

Key learning objectives are listed below:

  • Lead and organize Information Technology (IT) implementations at companies and institutions.
  • Invent and improve algorithms for storing, accessing, processing, and analyzing collected data.
  • Invent real-time computation methods for analysis and processing of data in robotics (optical, sound, and other real-time data from digital sensors).
  • Create innovative and useful features for modern operating systems (multiprocessor, multiprocessing, distributed).
  • Contribute to research and development of algorithms in all areas that are now and in the future subject to computerization.
  • Clearly explain Computer Science concepts in research, development, and educational institutions.
  • Show proficiency and skills in the most important areas of state of the art computer science.

Applicants must possess a bachelor’s degree with a minimum cumulative GPA of 2.75, or a master’s degree with a minimum cumulative GPA of 3.0.

Applicants whose native language is not English may be asked to submit evidence of English proficiency.

Please visit the USTSV Degree Programs' Admissions page for more information on how to apply for this program.

The structure of USTSV’s MSCSE degree programs is unique in its flexibility and ability to integrate the latest technological advances in Silicon Valley. Our instructors introduce new content and emerging best practices as they appear in the professional environment, thereby arming its students with the knowledge and skills necessary to be successful in their careers. By the end of the program, the curriculum will have not only covered the material of a traditional degree program, but also developed a strong foundation of real-world skills in computer science and engineering.

Artificial Intelligence (AI)

The MSCSE Artificial Intelligence degree program equips students to identify potential AI applications and develop and deploy AI solutions to large practical problems and provides a through grounding in machine learning, neural networks, natural language processing and deep learning.

Data Science

The MSCSE - Data Science degree program provides students with a core background in Computer Science and specialized algorithmic, statistical, and systems expertise in acquiring, storing, accessing, analyzing and visualizing large, heterogeneous and real-time data associated with diverse real-world domains including energy, the environment, health, media, medicine, and transportation.

Software Engineering

The MSCSE Software Engineering degree program focuses on providing its graduates not only software development skills, but also systems engineering, team collaboration, and product management skills necessary for top-tier careers and for leadership in software engineering. It emphasizes education for the future, including such emerging trends as full stack software development, big data, cloud computing, test-driven development, agile methods, mobile and distributed network-centric architectures.

VLSI Design

The MSCSE VLSI Design degree program is tailored to meet the needs of today’s hardware engineers in Silicon Valley where the hardware manufacturing process is without boundaries. It provides the in-depth and interdisciplinary skills required to understand and develop new technologies and trends in electrical engineering; and to advance into professional leadership and shape the future of this dynamic field. The program focuses on a background in analysis, design, development, or research on electrical or computer engineering in a variety of technical areas.

A minimum of 36 trimester units of graduate study are required for the MSCSE program. They include a few required foundation courses, a set of major-specific courses based on a student’s chosen major, a required capstone course, and elective courses. The MSCSE coursework is to develop technical skills beneficial to a student for his/her career development. Students also have the opportunity to take elective courses outside of computer science and engineering to broaden their skills.

A student must meet prerequisite requirements when taking any course. Upon clearing background preparation work, the student starts to take courses to meet the degree requirements. The student must begin his/her graduate study with the subjects listed in the Foundation Requirements section.

Foundation Requirements (9 units)

(Required subjects)

  • CSE500 Software Design and Implementations
  • CSE510 Fundamentals of Embedded Design
  • CSE520 Advanced Operating System

Major Course Requirements (12 units)

A student is advised to consider industry trends when selecting his/her major and its related courses. Before taking the Capstone Course (CSE599) near the end of the program, a student will have taken a minimum of 12 units of graduate level MSCSE courses and 12 units of electives. The following are examples of cluster courses for each major:

  • Artificial Intelligence:
    • CSE561 Foundations of Artificial Intelligence
    • CSE567 Machine Learning
    • CSE585 Practical Application of Deep Learning Theory
  • Data Science:
    • CSE540 Advanced Data Structure and Algorithms
    • CSE537 Foundations of Data Management
    • CSE558 Foundation of Data Science and Data Analytics
  • Software Engineering:
    • CSE540 Advanced Data Structure and Algorithms
    • CSE550 Advanced Java Programming for Internet Applications
    • CSE556 Database Design for Cloud-based Applications
    • CSE585 Large Scale Software Engineering and Process
  • VLSI Design:
    • CSE542 Embedded Software Design in Linux
    • CSE546 Device Driver Design
    • CSE562 Advanced Computer Networks
    • CSE575 VLSI Design

Selecting any four (4) courses from the above lists will meet the Major Requirements. Taking four (4) courses in a cluster area will also help the student develop desirable skills in that specialized software engineering profession.

Each trimester when the course offering list is published, instructions on graduate level courses belonging to various major areas are also published along with the course offering list. Every graduate student is advised to refer to these instructions to select courses and build his/her expertise area. In addition, a cross disciplinary study of majors can be desirable as the fast changing computer industry has become more demanding on engineers to have multidisciplinary skills.

Electives (12 units)

A student may take any graduate-level courses, including those outside of MSCSE, to meet the electives requirement of 12 units. When applicable, a student may take Curricular Practicum courses and engage in practical training to work on company projects that are directly related to the student’s course of study. No more than 6 units of practicum coursework may be counted towards graduation.

Capstone Course (3 units)

(A required subject)

Upon completing all or most coursework for this program, a student is required to take the capstone course and, under the guidance of the course instructor, integrate the knowledge and skills learned from all of the courses taken during the program.

  • CSE599 Computer Science Capstone Course

The MSCSE degree program requires a minimum of 36 units of graduate-level courses, in following categories:

  1. Foundation Requirements,
  2. Major Requirements,
  3. Electives, and
  4. A Capstone Course.

The following are required for graduation:

  • A graduate student admitted with under-graduate deficiencies must clear the deficiencies in the early terms. The student may clear a subject by either taking the course and earning a passing grade or passing a proficiency exam on the subject,
  • Maintain a grade of C- or better for all courses taken to clear deficiencies or towards the degree requirements,
  • Maintain an overall G.P.A. of 3.0 or better,
  • Maintain good standing with the University – with clear financial, library, and other school records,
  • The student is approved to graduate after filing a petition for graduation.

90%+ of graduates of USTSV’s MSCSE program have obtained jobs within three months of graduation.

Please visit Career Center page for more details.

The USTSV Computer Science and Engineering faculty is made up of experienced professionals from local industry-leading companies such as Google, Facebook, Apple and Intel, serial entrepreneurs from local startups, and educators from a diverse array of business backgrounds and disciplines in Silicon Valley. Each is dedicated to building a truly unique experience for MSCSE students. Although some MSCSE professors teach in other settings or have a daytime job in a high-tech company, you'll find that each faculty member teaches classes within a distinct MSCSE context, integrating material with that of other professors to create a cohesive learning experience in each theme. The program's faculty function as one team with a common objective - developing and refining your leadership skills. They meet regularly to coordinate materials, review content, and evaluate your progress.

Our faculty's work extends well beyond the case room and lecture hall. Many serve as local technology leaders, tech management executives, senior architects and engineers to a broad range of companies in Silicon Valley, both Fortune 500 and smaller. Some of them are serial entrepreneurs who have successfully started their own ventures. This is where much of our curriculum innovation comes from - our professors are in tune with what's really going in software and hardware advances in Silicon Valley. The inevitable intersection between practice and academia creates a learning environment that fosters both insight for innovative ways to improve the state of art in software and hardware as it is practiced today and foresight for future curriculum changes.

All information contained here is summarized from the USTSV Catalog and is considered non-official. For all rules, regulations, procedures, and outlines, please see the current academic year USTSV Catalog. The USTSV Catalog supersedes all other publications.