AI Minor at NJIT Creates a Foundation for All Students

The increasing need to explore the potential of artificial intelligence (AI) pervades every aspect of daily life and has created new opportunities for students across all levels to learn about what is becoming fundamental to transforming the modern business infrastructure.

Thanks to several recent additions to the faculty who bring the latest in leading-edge expertise in AI, the department of Data Science in the Ying Wu College of Computing (YWCC) has designed a series of AI courses that will provide a foundation for students from bachelor's to Ph.D. level with or without a background to develop fundamental knowledge.

The Minor in AI for non-data science and non-computer science majors and data science and computer science majors are both designed to provide students with foundational knowledge and practical skills in AI. Each program includes courses in machine learning, neural networks, data science, AI ethics and applications of AI in other fields.

The graduate level offerings will further enrich the existing M.S. in Artificial Intelligence and its corresponding graduate certificate.

The new courses support the emerging trend of AI + X as a bridge across the spectrum of different disciplines and industries.

"With new faculty and courses, we are continuing to leverage our resources to lead in many areas of AI education and research," said Hai Phan, associate chair in the department of Data Science. "We have a commitment to excellence in AI education, which is in line with the university's strategic plan. This is just the beginning."

The department expects to add a B.S. in Artificial Intelligence in approximately two years.

Approved Undergraduate Courses:

• DS 100 (GER) Basic Foundations of Data Science
• DS 110 (GER) Basic Foundations of Artificial Intelligence
• DS 400 Scientific Foundations of Machine Learning
• DS 410 Federated Machine Learning and Applications
• DS 480 Fundamentals and Applications of Graph Neural Networks
• DS 487 Artificial Intelligence for Temporal Data

Approved Graduate Courses

• DS 633 Advances in Representation Learning
• DS 681 Deep Learning for Computer Vision
• DS 685 AI for Robotics
• DS 688 Advanced Federated Learning
• DS 732 Theoretical Foundation of Machine Learning
• DS 687 Artificial Intelligence for Temporal Data