1. MCS Master of Computer Science Program
Michael Goodrich
Chancellor’s Professor

2. Comparing MCS and MSCS Degrees
The MCS is primarily an
on-campus program

3. Hiring summer interns and graduates
MCS
Communication/Cooperation with Industry is important
We welcome input from the ICS Leadership Council
Especially with respect to:
Providing input and feedback on program direction and with respect to our Capstone Design Projects.
Hiring summer interns and graduates

4. MCS Program Characteristics Faculty Characteristics
Every course has a strong lab/project component and teaching support from seasoned PhD students and readers (graders)
Students complete a full-time capstone design and professional communication experience in the fourth quarter of the program
The first cohort is all full time
The second cohort will allow for some part time students
Faculty Characteristics
Almost all are CS faculty in the Bren School of ICS (mostly Senate faculty)
A couple are visiting faculty
In the future a few could be high-level industry professionals with graduate degrees

5. MCS Student Characteristics
The first class will have approx. 100 students
The first class is mainly non-resident, possibly due to strong demand from overseas
Most students are from CS or closely related fields – though we anticipate taking outstanding students from other technical fields in the future

6. MCS Master of Computer Science Program
Questions?
Faculty Director – Amelia Regan

7. MCS Required Courses Principles of Applied Data Management
Computer Systems Architecture or Operating Systems
Fundamentals of Algorithms with Applications
Capstone Professional Writing and Communication for Computer Science Careers
Capstone Design Project for Computer Science

8. MCS
Elective Courses (6 of the following -- not all courses offered every year)
Applied Cryptography
Network and Distributed Systems Security
Principles of Scientific Computing
Computer Graphics and Visualization
Visual Computing
Distributed Computer Systems
Computer and Communications Networks
Introduction to IoT
Operating Systems
Computer Systems Architecture
Data Structures with Applications
Introduction to Optimization
Introduction to Artificial Intelligence
Machine Learning and Data Mining

9. MCS Learning outcomes Assessment
An ability to communicate effectively in written form regarding topics in the discipline
An ability to use current techniques, skills, and tools necessary for computing practices
An ability to apply mathematical foundations and algorithmic principles in the modeling, design, and analysis of computer-based systems
An ability to apply design and development principles in the construction of computationally based systems of varying complexity
Assessment
Course Performance
Capstone Projects
Placements
Exit Surveys (and 3 and 5 year surveys)
Employer Surveys