Abstract:

This paper presents the redesign of an undergraduate analytics practicum course that integrates generative AI, AI-assisted data visualization, and advanced AI-based analytics methods into a real-world, project-based learning environment. Simulating a real-world analytics consulting project in collaboration with an external industry partner, students analyze various authentic datasets and address applied business challenges.

A comparative case study evaluates student learning outcomes before and after the AI-driven curriculum redesign. Assessment measures include technical proficiency, domain knowledge, model development, visualization effectiveness, quality of insights, and presentation performance. Findings indicate that embedding AI-supported workflows alongside structured visualization and analytics methodologies enhances student engagement, strengthens analytical reasoning, and improves the clarity, interpretability, and depth of data-driven recommendations within a novel context (i.e., healthcare) that students were not previously familiar with. The study provides a practical framework for modernizing analytics education in alignment with evolving industry expectations and technological advancements.

Keywords:

Artificial Intelligence in Education, Experiential Learning, Analytics Education.