A Course on Applied AI and Data Science

Artificial intelligence (AI) and data science have become one of the most popular curricula in the computing educations. Plenty of theories, optimizations and math are involved in these courses, which results in a higher degree of difficulty for students to learn, not to mention the students without specializations in computer science or information technology. Beyond the complicated knowledge and theories, students may prefer to learn and focus on applied AI or data science which refer to the knowledge or skills for practical problem-solving and real-world applications. For example, information retrieval has been listed as one of the curricula in several undergraduate and/or graduate programs in the AI or data science programs. This paper describes a course that focuses on the topic of recommender systems which is in high demand in both academia and industries. This course has been extremely successful at the authors' institutions. In this paper, we introduce the course's objectives, structure and methodologies, discuss possible ways to deliver hands-on practice, summarize the outcomes, and finally present the lessons learned, as well as the feedbacks from the students. These experience could be useful and may give advice to other educators looking to create a similar course in their program.