Computer Science Master of Science
Leading to a Master of Science Degree in Computer Science
Gain the expertise to drive innovation with Wentworth's Master's in Computer Science. Our program provides advanced training in AI, machine learning, software engineering, cloud services, Parallel Computing, LLMs, and more, preparing you for leadership positions in tech, finance, healthcare, and other dynamic fields.
Program Educational Objectives
At the end of this program, students will be able to:
- Model, analyze, and design computing processes and systems
- Demonstrate mastery of leading-edge techniques and technologies
- Evaluate current and emerging issues in computing
Student Outcomes
Graduates of the Master of Science in Applied Computer Science graduates will:
- Demonstrate and function effectively in a team, engage in the process of modeling, designing, and implementing computer-based systems of varied complexity utilizing multiple technologies.
- Maintain effective communication with stakeholders in a typical software development environment by preparing and delivering effective technical presentations using appropriate technologies writing clear and accurate technical documents.
- Learn new models, techniques, and technologies as they emerge, and appreciate the necessity for continuing professional development.
- Demonstrate an ability to model, analyze and design computing processes and systems.
- Analyze a current significant software technology, articulate its strengths and weaknesses, and specify and promote improvements or extensions to that technology.
- Recognize and analyze social and professional issues and responsibilities faced by computing professionals.
Total: 30 credits. The program consists of 4 Core courses and 6 Electives.
CORE COURSES:
| Course | Title | Credits |
|---|---|---|
| COMP7010 | ADVANCED ALGORITHMS | 3 |
| COMP7431 | ADVANCED SOFTWARE ENGINEERING | 3 |
| COMP6710 | PRINCIPLES OF MACHINE LEARNING | 3 |
| COMP6999 | TECHNICAL PROJECTS DEVELOPMENT | 3 |
| Total Credits | 12 | |
Electives:
| Course | Title | Credits |
|---|---|---|
| COMP5705 | DATA MINING | 3 |
| COMP5750 | EMBEDDED ARTIFICIAL INTELLIGENCE | 4 |
| COMP5775 | ADVANCED PARALLEL COMPUTING | 4 |
| COMP6100 | SECURE SOFTWARE DEVELOPMENT | 3 |
| COMP6760 | COMPUTER VISION | 3 |
| COMP7025 | Sports Analytics | 4 |
| COMP7350 | BIG DATA SYSTEMS | 3 |
| COMP7600 | THESIS | 3 |
| COMP7800 | GRADUATE SPECIAL TOPICS IN APPLIED COMPUTER SCIENCE | 4 |
| AAIN5720 | TRUSTWORTHY GENERATIVE AI | 3 |
| AAIN7001 | FOUNDATIONS OF ARTIFICIAL INTELLIGENCE | 3 |
| AAIN7410 | AGENTIC AI SYSTEMS | 3 |
| AAIN7420 | DATA ENGINEERING FOR AI | 3 |
| AAIN7422 | EXPLAINABLE ARTIFICIAL INTELLIGENCE | 3 |
| AAIN7424 | INTELLIGENT SYSTEMS | 3 |
| AAIN7430 | PROMPT ENGINEERING | 3 |
| DATA6150 | DATA SCIENCE FOUNDATIONS | 3 |
| DATA6000 | APPLIED STATISTICS FOR RESEARCH | 3 |
| DATA6100 | DATA VISUALIZATION | 3 |
| DATA6200 | DATA MANAGEMENT | 3 |
| DATA6300 | ADVANCED TOPICS IN LARGE LANGUAGE MODELS | 3 |
| DATA6710 | APPLIED DEEP LEARNING | 3 |
| DATA6999 | CAPSTONE | 3 |
| DATA7800 | GRADUATE SPECIAL TOPICS | 4 |
| MATH5700 | MATHEMATICS FOR MACHINE LEARNING | 3 |
| MATH7800 | GRADUATE SPECIAL TOPICS IN APPLIED MATHEMATICS | 1-4 |
| CYBR6420 | REVERSE ENGINEERING | 3 |
| CYBR6520 | MALWARE ANALYSIS | 3 |
| CYBR6550 | THREAT INTELLIGENCE | 3 |
| CYBR6580 | DIGITAL FORENSICS AND INCIDENT RESPONSE | 3 |