Applied Computer Science Master of Science
Leading to a Master of Science Degree in Applied Computer Science
Artificial Intelligence (AI) & Machine Learning (ML) have revolutionized the way we live and work. As organizations continue to find new uses for this exciting technology, the demand for computer scientists trained in their application continues to skyrocket. The thesis-based Master of Science in Applied Computer Science, with concentration in AI, gives students the theoretical and practical skills needed to advance their career and stand out in today’s competitive job market. The Master of Science in Applied Computer Science is available in a 4+1 specifically for computer science or closely related majors at Wentworth students completing eight credits of gradute level courses during their senior spring and summer semesters, a 2-Year program which is a more traditional masters degree for students with a baccalaureate degree in computer science or related field, and a 3-Year program which prepares students who have little or no programming experience for entry into the 2-Year program, further allowing any student regardless of their background, to pursue a Master of Science in Applied Computer Science degree.
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.
4 +1 Masters of Science in Applied Computer Science: Requirements which include two courses ( 8 credits) completed during senior year and one additional graduate year starting in the fall. 32 credits
| Course | Title | Credits |
|---|---|---|
| Spring Semester: Undergraduate Senior Year | ||
| COMP5050 | MODERN COMPUTING | 4 |
| Summer Semester: Undergraduate Senior Year | ||
| COMP5700 | CLASSICAL ARTIFICIAL INTELLIGENCE | 4 |
| Grade of B or higher required in undergraduate courses to satisfy requirements in the Master of Science in Applied Computer Science | ||
| Year One: Fall | ||
| COMP5705 | DATA MINING | 3 |
| or COMP5710 | PRINCIPLES OF MACHINE LEARNING | |
| AI Elective 2 | 3 | |
| AI Elective 2 | 3 | |
| COMP7500 | THESIS I | 3 |
| Spring | ||
| AI Elective 2 | 3 | |
| ACS Elective 3 | 3 | |
| General Elective 1 | 3 | |
| COMP7550 | THESIS II | 3 |
| Total Credits | 32 | |
2-Year Program Master of Science in Applied Computer Science: Requirements for students with a baccalaureate degree in computer science, or related field.
35 credits
| Course | Title | Credits |
|---|---|---|
| Year 1: Fall | ||
| COMP5050 | MODERN COMPUTING | 4 |
| General Elective 1 | 3 | |
| MATH5750 | APPLIED STATISTICS | 4 |
| Spring | ||
| COMP5700 | CLASSICAL ARTIFICIAL INTELLIGENCE | 4 |
| AI Elective 2 | 3 | |
| ACS Elective 3 | 3 | |
| Year 2: Fall | ||
| COMP5705 | DATA MINING | 3 |
| or COMP5710 | PRINCIPLES OF MACHINE LEARNING | |
| AI Elective 2 | 3 | |
| COMP7500 | THESIS I | 3 |
| Spring | ||
| AI Elective 2 | 3 | |
| COMP7550 | THESIS II | 3 |
| Total Credits | 35 | |
3-Year Program Master of Science in Applied Computer Science: Requirements for students with any baccalaureate degree to earn a Masters of Science in Applied Computer Science. 55 credits
| Course | Title | Credits |
|---|---|---|
| Year 1: Fall | ||
| COMP5900 | PROGRAMMING FUNDAMENTALS | 6 |
| MATH5200 | METHODS OF CALCULUS | 4 |
| Spring | ||
| COMP5925 | DATA STRUCTURES & ALGORITHMS | 6 |
| MATH5750 | APPLIED STATISTICS | 4 |
| Year 2: Fall | ||
| COMP5050 | MODERN COMPUTING | 4 |
| MATH5700 | MATHEMATICS FOR MACHINE LEARNING | 3 |
| General Elective 1 | 3 | |
| Spring | ||
| COMP5700 | CLASSICAL ARTIFICIAL INTELLIGENCE | 4 |
| AI Elective 2 | 3 | |
| ACS Elective 3 | 3 | |
| Year 3: Fall | ||
| COMP5705 | DATA MINING | 3 |
| or COMP5710 | PRINCIPLES OF MACHINE LEARNING | |
| AI Elective 2 | 3 | |
| COMP7500 | THESIS I | 3 |
| Spring | ||
| AI Elective 2 | 3 | |
| COMP7550 | THESIS II | 3 |
| Total Credits | 55 | |