Computer Science, Master of Science (MS)
The Master’s Program in Computer Science has been designed to provide opportunities for professional growth in this rapidly changing field. The program strives to provide a balance between practical applications-oriented content and a theoretical framework for continued learning.
| Required Core–this coursework provides core knowledge in the areas of algorithms, software engineering, and research methods. | ||
| CSCD 501 | ADVANCED ALGORITHMS | 5 |
| CSCD 524 & 524L | ADVANCED SOFTWARE ENGINEERING and ADVANCED SOFTWARE ENGINEERING LAB | 4 |
| CYBR 515 | RESEARCH METHODS AND COLLOQUIUM | 4 |
| Electives–choose five courses–at least two must be at the 500-level | 20 | |
| Note: This coursework provides the student an opportunity to take courses specialized to their particular area(s) of interest. Any 400-level or non-CSCD course must be approved by the CSCD graduate coordinator or the student’s graduate committee chair. CSCD 695 cannot be used to satisfy any portion of these elective requirements. CSCD 539 may apply more than once, provided distinct topics are studied. CSCD 595 may only be applied as a single elective. | ||
| Thesis or Project | ||
| Note: The student is expected to expand their knowledge with a published thesis or to apply their knowledge to a significant project. Projects may be work-related. The thesis or project is defended in a final oral examination of the student’s work. | ||
| CSCD 600 | THESIS (1-16 variable credit) | 16 |
| or CSCD 601 | RESEARCH REPORT | |
| Total Credits | 49 | |
| Approved Electives | ||
| CSCD 527 & 527L | MODERN DATABASE SYSTEMS and MODERN DATABASE SYSTEMS LAB | 4 |
| CSCD 529 & 529L | DATA MINING and DATA MINING LAB | 4 |
| CSCD 530 & 530L | BIG DATA ANALYTICS and BIG DATA ANALYTICS LAB | 4 |
| CSCD 539 | TOPICS IN COMPUTER SCIENCE | 4 |
| CSCD 545 & 545L | GPU COMPUTING and GPU COMPUTING LAB | 4 |
| CSCD 567 & 567L | CLOUD FOUNDATION AND PROGRAMMING and CLOUD FOUNDATION AND PROGRAMMING LAB | 4 |
| CSCD 570 & 570L | 3D COMPUTER GRAPHICS PRINCIPLES and 3D COMPUTER GRAPHICS PRINCIPLES LAB | 4 |
| CSCD 573 & 573L | DATA VISUALIZATION and DATA VISUALIZATION LAB | 4 |
| CSCD 574 & 574L | GAME DESIGN AND DEVELOPMENT 1 and GAME DESIGN AND DEVELOPMENT 1 LAB | 4 |
| CSCD 575 & 575L | GAME DESIGN AND DEVELOPMENT 2 and GAME DESIGN AND DEVELOPMENT 2 LAB | 4 |
| CSCD 577 & 577L | VIRTUAL REALITY WITH COMPUTER GRAPHICS AND GAME ENGINES and VIRTUAL REALITY WITH COMPUTER GRAPHICS AND GAME ENGINES LAB | 4 |
| CSCD 580 & 580L | INTELLIGENT SYSTEMS and INTELLIGENT SYSTEMS LAB | 4 |
| CSCD 583 & 583L | MODELING AND SIMULATION and MODELING AND SIMULATION LAB | 4 |
| CSCD 584 & 584L | MACHINE LEARNING and MACHINE LEARNING LAB | 4 |
| CSCD 585 & 585L | DEEP LEARNING and DEEP LEARNING LAB | 4 |
Plan of Study
Courses could be offered in different terms, checking with the academic department is paramount in keeping an individual plan current.
| First Year | |||||
|---|---|---|---|---|---|
| Fall Quarter | Credits | Winter Quarter | Credits | Spring Quarter | Credits |
| CYBR 515 | 4 | CSCD 501 | 5 | CSCD 524 & 524L | 4 |
| Computer Science Elective1 | 4 | Computer Science Elective1 | 4 | Computer Science Elective1 | 4 |
| 8 | 9 | 8 | |||
| Second Year | |||||
| Fall Quarter | Credits | Winter Quarter | Credits | Spring Quarter | Credits |
| CSCD 600 or 601 | 4 | CSCD 600 or 601 | 4 | CSCD 600 or 601 | 8 |
| Computer Science Elective1 | 4 | Computer Science Elective1 | 4 | ||
| 8 | 8 | 8 | |||
| Total Credits 49 | |||||
- 1
Electives–choose five courses–at least two must be at the 500-level. This coursework provides the student an opportunity to take courses specialized to their particular area(s) of interest. Any 400-level or non-CSCD course must be approved by the CSCD graduate coordinator or the student’s graduate committee chair. CSCD 695 cannot be used to satisfy any portion of these elective requirements. CSCD 539 may apply more than once, provided distinct topics are studied. CSCD 595 may only be applied as a single elective.
Students who earn an MS in Computer Science from EWU should be able to:
- analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions;
- apply computer science theory and software development fundamentals to produce computing-based solutions;
- communicate effectively in a variety of professional contexts.