Learner Reviews & Feedback for AI Applications in Marketing and Finance by University of Pennsylvania
About the Course
Top reviews
SP
Mar 23, 2025
Excellent details about how AI and ML are applied to specific use cases.
IW
Jun 27, 2025
Great to learn more about how AI apply in Marketing & Finance Industry
76 - 89 of 89 Reviews for AI Applications in Marketing and Finance
By William S
•Jul 19, 2022
finance and fraud applications were most interesting
By Gary Q
•May 20, 2025
Well paced and good examples of AI Implementation
By Ralph F
•Jun 11, 2024
Good general overview and intro to AI concepts.
By PALAK T
•Mar 20, 2025
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By Ryan R
•Aug 8, 2025
This course was interesting, but probably would be better divided into two courses (one for Marketing and one for Finance). The Marketing section mostly focused on the customer journey and predictive use cases of AI, but I would have loved a deeper exploration into other applications, including use of Generative AI for creative and the considerations that go along with it. At times, the Finance section felt like more of a statistics course than an AI course, and, like the Marketing section, there were opportunities to dive deeper into additional use cases.
By Abraham Z
•Sep 29, 2025
Good video quality, dialogue and pace. A bit too academic, and a bit too general about statistical analysis and machine learning (removed from the specific context of AI and of more current applications of it).
By Alvaro M
•Feb 3, 2025
Good introductory class. The material was more superficial than I expected and a bit dated.
By Silvio G
•Mar 20, 2025
Old content, very few on AI applications
By Kevin B
•May 7, 2025
no hands on work but informative
By Susan S
•Sep 19, 2025
Needs some updating for 2025
By TIna S
•Jan 9, 2026
The course positioning did not match the actual content. While marketed as AI Applications in Marketing and Finance, the marketing coverage focused on a narrow subset of topics, primarily personalization and recommendations, without addressing the broader marketing skill set practitioners need, such as measurement, experimentation, creative optimisation, attribution, or lifecycle strategy. The finance content was even less aligned for a marketing audience. Rather than covering financial literacy or decision-making skills useful for marketers, such as forecasting, budgeting, ROI modelling, or commercial trade-offs, the course leaned heavily into credit risk, fraud detection, and machine learning techniques more relevant to finance specialists and risk teams. Much of the material sat at a high-level conceptual layer or focused on ML mechanics, rather than helping learners understand how to apply AI strategically within real marketing or commercial contexts. As a result, the course felt fragmented, with limited cohesion between marketing and finance, and weak alignment to the practical needs implied by the course title. Clearer audience definition and tighter alignment between objectives, content, and real-world application would significantly improve the learning experience.
By Patrice A
•Aug 16, 2025
This is good for someone that is new to business and not familiar with any systems. Otherwise the content appears to be dated.
By Ellinor G
•Oct 3, 2025
If this is the level of Wharton today maybe we need to reconsider a few things…. Extremely disappointing course, the intellectual rigor and the engaging teaching are nowhere to be seen here, all you get are long and boring PPTs and examples that take forever to get to the point. If you’ll fall asleep while listening to this I won’t blame you…
By Bill F
•Jun 18, 2025
Finance/Credit risk analysis had virtually nothing to do with AI ... AI was mentioned in passing at the end.