Requirements for Masters of Science in Computing, Entrepreneurship and Innovation

The MS-CEI degree requires 13 courses (33 credits) including 4 courses taken at The Stern School of Business and 9 courses taken in Computer Science at the Courant Institute of Mathematical Sciences. The degree will be completed in one and a half years and students must enroll full time.

In addition, students must maintain good standing throughout their studies. This involves sustaining a grade-point average of at least 3.0 (B) each semester, and successfully completing at least two thirds of all courses attempted. Students falling below the GPA and course completion requirements are placed on probation, and given until the following fall or spring semester to return to good standing, or faced with possible academic dismissal from the program.

The MS-CEI degree has a unique course structure that will require students to take courses in these areas:

• An introductory course on Design and Innovation
• 4 business classes on core aspects of entrepreneurship
• 2 courses on systems engineering
• 2 application electives in computer science
• 1 elective on mathematical techniques and statistics
• 2 core courses on Lean Launchpad and Entrepreneurship Capstone
• 1 course on Agile development and DevOps

Many of the design and entrepreneurship classes are core classes and the courses have a well-defined structure. Through the entrepreneurship courses, MS-CEI students will:

• Learn core design and innovation principles of highly successful startups
• Gain a comprehensive understanding of technology opportunity identification and implementation
• Learn the customer-focused approach to product development
• Provide students with entrepreneurial business skills for venture creation
• Learn Agile Development and Operations practices
• Integrate the key principles of entrepreneurship and technology development

Through the one year program cycle, the design and entrepreneurship courses are structured that students will have the experience of developing their own startup idea across the entire cycle including: idea incubation, Minimum Viable Product (MVP) design, customer discovery, MVP development, Lean Launchpad, MVP refinement, pitching the startup idea, venture financing and company formation.

The computer science courses are designed specifically to teach the essential CS fundamentals essential to make the students technically very strong in mathematical and statistical techniques and computer systems development. Students can choose two application electives among advanced CS classes that best suit their technology interests.

The course plan is structured in a defined order as follows (schedule subject to change at anytime):

Fall semester (12 credits)

• MGMT-GB 2129 Founding a Startup (1.5 credits)
• COR1-GB 2103 Strategy (1.5 credits)
• CSCI-GA 2630 Foundations of Networks and Mobile Systems (3 credits)
• CSCI-GA 2810 Design and Innovation (3 credits)
• Elective in Mathematical Techniques and Statistics (3 credits)

Spring semester (12 credits)

• COR1-GB 2105 Communication (1.5 credits)
• COR1-GB 1102 Leadership in Organizations (1.5 credits)
• CSCI-GA 2820 DevOps and Agile Methodologies (3 credits)
• CSCI-GA 2830 Lean LaunchPad (3 credits)
• Elective in Systems Engineering (3 credits)

Fall semester (9 credits)

• CSCI-GA 2840 Entrepreneurship Capstone (3 credits)
• Two Electives in Applications (6 credits)

The following courses can be chosen for the Mathematical Techniques and Statistics Elective (3 points)

• CSCI-GA 1180 Mathematical Techniques for Computer Science Applications
• CSCI-GA 2565 Machine Learning
• CSCI-GA 2566 Foundations of Machine Learning
• CSCI-GA 2572 Deep Learning
• CSCI-GA 2112 Scientific Computing
• CSCI-GA 2271 Computer Vision
• CSCI-GA 2945 Advanced Topics in Numerical Analysis (Convex and Nonsmooth Optimization)
• CSCI-GA 2945 Advanced Topics in Numerical Analysis (Numerical Optimization)
• CSCI-GA 3003 Advanced Machine Learning
• CSCI-GA 3033 Mathematics of Deep Learning
• CSCI-GA 3033 Statistical NLP
• CSCI-GA 3033 Vision Meets Machine Learning
• CSCI-GA 3210 Introduction to Cryptography
• CSCI-GA 3520 Honors Analysis of Algorithms*

The following courses can be chosen for the Systems Engineering Elective (3 points)

• CSCI-GA 2130 Compiler Construction
• CSCI-GA 2434 Advanced Database Systems
• CSCI-GA.2436 Realtime and Big Data Analytics
• CSCI-GA 2620 Networks and Mobile Systems
• CSCI-GA 2621 Distributed Systems
• CSCI-GA 2630 Foundations of Networks and Mobile Systems
• CSCI-GA 3033 Abstract Interpretation
• CSCI-GA 3033 Big Data and ML Systems
• CSCI-GA 3033 Cryptocurrencies and Decentralized Ledgers
• CSCI-GA 3110 Honors Programming Languages*

The following courses can be chosen for the Applications Electives (6 points)

• CSCI-GA 2270 Computer Graphics
• CSCI-GA 2271 Computer Vision
• CSCI-GA 2274 Advanced Computer Graphics
• CSCI-GA 2560 Artificial Intelligence
• CSCI-GA 2565 Machine Learning
• CSCI-GA 2566 Foundations of Machine Learning
• CSCI-GA 2590 Natural Language Processing
• CSCI-GA 2565 Heuristic Problem Solving
• CSCI-GA 3033 Special Topics in Computer Science (sections of this course would be accepted if the content is appropriate)
• CSCI-GA 3110 Honors Programming Languages*
• CSCI-GA 3205 Applied Cryptography and Network Security
• CSCI-GA 3210 Introduction to Cryptography
• CSCI-GA 3220 Advanced Cryptography
• CSCI-GA 3250 Honors Operating Systems*

• * Requires department permission

• For a complete list of approved electives, see the MS-CEI Degree Requirements Form.