Graduate Learning Outcomes

The following learning outcomes define the knowledge, skills and competencies students are expected to demonstrate upon completion of their respective graduate programs in the Department of Computer Science at Bowling Green State University.

M.S. in Computer Science

Upon completion of the M.S. in Computer Science, students will be able to:

• Perform research, discovery and integration by applying advanced knowledge of computer science
• Critically analyze a body of current, published research in area of computer science
• Evaluate algorithmic and/or software-based solutions to a given problem

M.S. in Software Engineering

Upon completion of the M.S. in Software Engineering, students will be able to:

• Solve complex software engineering problems by applying software engineering principles;
• Communicate effectively with a range of audiences;
• Collaborate effectively on software engineering teams.

M.S. in Data Science

Upon completion of the M.S. in Data Science, students will be able to:

• Evaluate computational and statistical methods for analyzing complex and large-scale datasets.
• Design data-driven models and algorithms to address real-world problems and support decision-making.
• Communicate analytical findings effectively to technical and non-technical audiences.

Ph.D. in Data Science

Upon completion of the Ph.D. in Data Science, students will be able to:

• Demonstrate competency in the core concepts and techniques of data science, which come from both computer science and statistics.
• Demonstrate the ability to use or develop appropriate techniques to analyze structured, unstructured, or dynamic datasets.
• Demonstrate an understanding of the principles that underlie analytical methods, to articulate the strengths and limitations of analytical methods, and to defend choices to use some methods over others.
• Demonstrate the ability communicate effectively to technical and non-technical audiences orally, in writing, and with effective visualization.
• Demonstrate the ability to identify and respond to ethical concerns with the provenance and use of data.
• Demonstrate the ability to develop new techniques for the analysis of complex datasets or real-time modeling and decision-making, or extend existing techniques to novel and challenging datasets.
• Demonstrate the ability to organize data using tools appropriate to the problem, code new techniques in the appropriate computer language, optimize for performance and scalability, and distribute new tools to the data science community in a usable form.

"Graduate research" is a process of directed independent investigation or discovery driven by a narrowly focused question and sustained by a well-defined procedure capable of generating an answer to that question.