Bachelor of Science in Artificial Intelligence Engineering

Description

A Bachelor of Science in Artificial Intelligence Engineering (BS AIE) is an interdisciplinary undergraduate degree program that combines principles from mathematics, engineering, computer science, and other related fields to equip students with the knowledge and skills necessary to design, develop, innovate, and deploy artificial intelligence (AI) systems and technologies. This program typically provides students with a thorough understanding of various aspects of AI Engineering, including machine learning, neural networks, natural language processing, computer vision, robotics, data analytics, and more. Students learn to employ mathematical and statistical techniques to analyze and interpret data, as well as to develop algorithms and models that enable machines to learn from data and make intelligent decisions.

Program Educational Objectives

Within five (5) years after graduation, graduates of the program shall have:

• Undertaken, singly or in teams, projects that show ability to solve complex artificial intelligence engineering problems.
• Had substantial involvement in projects that take into consideration safety, health, environmental concerns and the public welfare, partly through adherence to required codes and laws.
• Demonstrated professional success via promotions and/or positions of increasing responsibility.
• Demonstrated life-long learning via progress toward completion of an advanced degree, professional development/continuing education courses, or industrial training courses.
• Exhibited professional behavior and attitude in artificial intelligence engineering practice.
• Initiated and implemented actions toward the improvement of artificial intelligence engineering practice.

Program Outcomes

By the time of graduation, the student shall have developed:

1. Apply knowledge of mathematics, natural science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
2. Conduct investigations of complex engineering problems using research-based knowledge and research methods, including design of experiments, analysis and interpretation of data, and synthesis of information to provide valid conclusions.
3. Design solutions for complex engineering problems and design systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.
4. Function effectively as an individual and as a member or leader of diverse teams and in multidisciplinary settings.
5. Identify, formulate, research literature, and analyze complex engineering problems, reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
6. Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice.
7. Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
8. Understand and evaluate the sustainability and impact of professional engineering work in the solution of complex engineering problems in a societal and environmental context.
9. Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
10. Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal, and cultural issues and the consequent responsibilities relevant to professional engineering practice and solutions to complex engineering problems.
11. Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, to complex engineering problems with an understanding of the limitations.
12. Demonstrate knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
13. Apply knowledge of artificial intelligence engineering in at least one specialized field of artificial intelligence engineering practice.