MSIT3101

INDUSTRY/CREATIVE APP GEN AI

This course is offered in a current or upcoming term. Check the official course schedule before registering.
Terms offered
3
Data refreshed
Jun 27, 2026

Description

This course provides an in-depth exploration of how Generative AI is utilized in creative fields such as digital art, music, and design, as well as its applications to enhance productivity and performance in business settings. Through a blend of theoretical discussions and hands-on projects, students will examine innovative ways in which Generative AI algorithms transform traditional creative processes, enabling artists, musicians, and designers to push the boundaries of their craft. Additionally, students will explore case studies and real-world examples highlighting the integration of Generative AI in various industries, from marketing and advertising to finance and healthcare, gaining insights into how these technologies can improve efficiency, streamline workflows, and unlock new opportunities for product innovation and growth. By the end of the course, students will emerge with a deep understanding of the diverse applications of Generative AI and the skills to leverage its potential to revolutionize both creative expression and business operations.

Syllabi

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Offering history & forecast 2025–2026

2025
2026
Sections offered by academic year and season, with estimated offering chances for future years above the divider
YearFallSpringSummerIntersession
2030 2030 Fall: not enough history to forecast. 2030 Spring: not enough history to forecast. 2030 Summer: 7% chance, medium confidence. Offered in 0 of 9 summer terms since 2018. 2030 Intersession: 8% chance, medium confidence. Offered in 0 of 6 intersession terms since 2020.
2029 2029 Fall: not enough history to forecast. 2029 Spring: not enough history to forecast. 2029 Summer: 6% chance, medium confidence. Offered in 0 of 10 summer terms since 2017. 2029 Intersession: 7% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017.
2028 2028 Fall: not enough history to forecast. 2028 Spring: not enough history to forecast. 2028 Summer: 5% chance, medium confidence. Offered in 0 of 11 summer terms since 2016. 2028 Intersession: 7% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017.
2027 2027 Fall: not enough history to forecast. 2027 Spring: not enough history to forecast. 2027 Summer: 5% chance, high confidence. Offered in 0 of 12 summer terms since 2015. 2027 Intersession: 6% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017.
2026 1 section Not offered Not offered No data for this term
2025 1 section 2 sections Not offered Not offered
Forecast Under 15% 15–39% 40–69% 70–89% 90%+ Not enough history
Fall Spring Summer Intersession Darker means more sections Not offered No data for term

Future estimates combine recent offering frequency with detected multi-year cycles. Hover a cell for confidence and evidence; low-confidence estimates are marked with ~.

Meeting times

Most recent first
  • Tue, 6:30 PM–9:30 PM JC118 20262025
  • Wed, 6:30 PM–9:30 PM ONLINE 2025-1
  • Thu, 6:30 PM–9:30 PM ONLINE 2025-2
Credit-bearing sections of MSIT3101
TermProfessorTypeCreditsEnrollmentCRN
Fall 2026Shivansh Awasthi (He/Him)Online1 1 of 30 enrolled24047
Fall 2025Kevin C. KellerOnline1 10 of 30 enrolled24047
Spring 2025Kevin C. KellerOnline1 31 of 30 enrolled34009
Spring 2025Kevin C. KellerOnline1 13 of 30 enrolled34103