From self-driving cars to smart cities, we live in a hyper-connected world. As the smart thinkers behind today’s smart devices and systems, computer engineers hold the key to understanding, advancing, and protecting the security of next generation technologies and data networks.
The Master of Engineering, Plan C, Computer Engineering Specialization produces professionals with broad engineering backgrounds who are capable of applying in-depth knowledge and creativity to drive innovation in virtually any field. Students have flexibility to develop a plan of study in their area of interest. Students interested in graduate work should refer to CSU's Graduate and Professional Bulletin and the Electrical and Computer Engineering Department website.
Program Learning Objectives
- Identify, formulate, and solve advanced engineering problems using fundamental computer engineering principles, methodologies, and tools.
- Apply in-depth knowledge and creativity in a variety of contexts to achieve a significant engineering objective.
- Demonstrate effective oral and written communication to convey technical concepts to both engineers and non-engineers.
- Demonstrate professional behavior and understand the ethical, economic, environmental, and societal impacts of their work.
Institutional Learning Objectives
Program Learning Objectives (PLOs) align with and support the University’s Institutional Learning Objectives (ILOs), which are Creativity, Reasoning, Communication, Responsibility, and Collaboration.
Creativity: PLOs 1 and 2 ensure that students can creatively apply their disciplinary expertise to solve complex problems using fundamental computer engineering principles and methods.
Reasoning: PLOs 1 and 2 ensure that students can apply reasoning skills to solve complex problems using fundamental computer engineering principles and methods.
Communication: PLO 3 ensures that students demonstrate effective communication to a variety of audiences.
Responsibility: PLO 4 ensures that students exhibit responsible behavior according to professional standards.
Collaboration: PLOs 3 and 4 ensure that students demonstrate professional skills to engage collaboratively to solve problems in a societal context.
Effective Fall 2024
| Code | Title | Credits |
|---|---|---|
| Regular Coursework 1, 2, 3 | 30 | |
CS 4XX Any CS course at the 400-level (excluding courses numbered 482-499) | ||
CS 5XX Any CS course at the 500-level (excluding courses numbered 582-599) | ||
CS 6XX Any CS course at the 600-level (excluding courses numbered 682-699) | ||
ECE 4XX Any ECE course at the 400-level (excluding courses numbered 482-499) | ||
ECE 5XX Any ECE course at the 500-level (excluding courses numbered 582-599) | ||
ECE 6XX Any ECE course at the 600-level (excluding courses numbered 682-699) | ||
MATH 4XX Any MATH course at the 400-level (excluding courses numbered 482-499) | ||
MATH 5XX Any MATH course at the 500-level (excluding courses numbered 582-599) | ||
MATH 6XX Any MATH course at the 600-level (excluding courses numbered 682-699) | ||
PH 4XX Any PH course at the 400-level (excluding courses numbered 482-499) | ||
PH 5XX Any PH course at the 500-level (excluding courses numbered 582-599) | ||
PH 6XX Any PH course at the 600-level (excluding courses numbered 682-699) | ||
| Biomolecular Tools for Engineers | ||
| Engineering Optimization: Method/Application | ||
| Engineering Decision Support/Expert Systems | ||
| Engineering Risk Analysis | ||
| Spaceflight and Biological Systems | ||
| Stochastic Simulation in Engr Applications | ||
| Fundamentals of High Performance Computing | ||
| Introduction to Graduate Research | ||
| Ethical Conduct of Research | ||
| STEM Communication | ||
| Numerical Methods in Science and Engineering | ||
| Linear Algebra for Data Science: Matrices and Vectors Spaces | ||
| Linear Algebra for Data Science: Geometric Techniques for Data Reduction | ||
| Linear Algebra for Data Science: Matrix Factorizations and Transformations | ||
| Linear Algebra for Data Science: Theoretical Foundations | ||
| Advanced/Additive Manufacturing Engineering | ||
| Simulation Modeling and Experimentation | ||
| Principles of Dynamics | ||
| Advanced Mechanical Systems | ||
| Materials Engineering | ||
| Fundamentals of Robot Mechanics and Controls | ||
| Bioengineering | ||
| Solar and Alternative Energies | ||
| Biologically Inspired Robotics | ||
| Ethical Issues in Big Data Research | ||
| Probability with Applications | ||
| Foundations of Systems Engineering | ||
| Overview of Systems Engineering Processes | ||
| Dynamics of Complex Engineering Systems | ||
| Space Mission Analysis and Design | ||
| Engineering Data Design and Visualization | ||
| Secure Vehicle and Industrial Networking | ||
| Systems Engineering Architecture | ||
| Cybersecurity Awareness for Systems Engineers | ||
| Analytics in Systems Engineering | ||
| Ethics in Systems Engineering | ||
| Program Total Credits: | 30 | |
A minimum of 30 credits are required to complete this program.
- 1
Courses not accepted as regular include all courses ending in the range -82 through -99.
- 2
A maximum of 8 credit hours of 400-level undergraduate coursework can be counted to the degree. Remaining credits must be in 500-level or higher courses.
- 3
A maximum of 15 credit hours outside of the ECE department can be counted to the degree.
For more information, please visit Requirements for All Graduate Degrees in the Graduate and Professional Bulletin.
Summary of Procedures for the Master's and Doctoral Degrees
NOTE: Each semester the Graduate School publishes a schedule of deadlines. Deadlines are available on the Graduate School website. Students should consult this schedule whenever they approach important steps in their careers.
Forms are available online.
| Step | Due Date |
|---|---|
| 1. Application for admission (online) | Six months before first registration |
| 2. Diagnostic examination when required | Before first registration |
| 3. Appointment of advisor | Before first registration |
| 4. Selection of graduate committee | Before the time of fourth regular semester registration |
| 5. Filing of program of study (GS Form 6) | Before the time of fourth regular semester registration |
| 6. Preliminary examination (Ph.D. and PD) | Two terms prior to final examination |
| 7. Report of preliminary examination (GS Form 16) - (Ph.D. and PD) | Within two working days after results are known |
| 8. Changes in committee (GS Form 9A) | When change is made |
| 9. Application for Graduation (GS Form 25) | Refer to published deadlines from the Graduate School Website |
| 9a. Reapplication for Graduation (online) | Failure to graduate requires Reapplication for Graduation (online) for the next time term for which you are applying |
| 10. Submit thesis or dissertation to committee | At least two weeks prior to the examination or at the discretion of the graduate committee |
| 11. Final examination | Refer to published deadlines from the Graduate School Website |
| 12. Report of final examination (GS Form 24) | Within two working days after results are known; refer to published deadlines from the Graduate School website |
| 13. Submit a signed Thesis/Dissertation Submission Form (GS Form 30) to the Graduate School and Submit the Survey of Earned Doctorates (Ph.D. only) prior to submitting the electronic thesis/dissertation | Refer to published deadlines from the Graduate School website. |
| 14. Submit the thesis/dissertation electronically | Refer to published deadlines from the Graduate School website |
| 15. Graduation | Ceremony information is available from the Graduate School website |