Artificial Intelligence for Business Applications
NBA 4920/6921, Johnson Graduate School of Management, Cornell University, Spring 2025
| Instructor: Emaad Manzoor (emaadmanzoor@cornell.edu) | Office Hours: Tuesdays, 1-2PM, in Sage 367 |
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| Meeting Times and Locations: | Grading: Homework (30%), Midterm (30%), |
| Section 1: Tue/Thu 2.55-4.10PM, Breazzano 123 | Project (30%), Class Participation (10%) |
| Section 2: Tue/Thu 11.40AM-12.55PM, Breazzano 123 | Resources: Syllabus |
| Section 3: Tue/Thu 8.40-9.55AM, Breazzano 123 | Course Project: Requirements and Rubric |
About this course: Artificial intelligence is increasingly used to automate business decisions. This course demystifies artificial intelligence by providing students a conceptual, theoretical, and practical understanding of how artificial intelligence works, and what it can (and cannot) do well.
Which section should I enroll in? 4920 if you’re an undergrad. If you’re a grad student: 6921 (offered in the first half), or 6921 and 6925 (this is the advanced version of the course offered in the second half).
| Week | Topic | Resources & Assignments |
|---|---|---|
| Week 1 | Prediction Machines Course Goals & Logistics How Machines Learn Evaluating Artificial Intelligence Case Study: Fraud at AirBnb |
Teachable Machine QuickDraw Homework 1: Evaluating AI |
| Week 2 | Generative Artificial Intelligence Training Stochastic Parrots Learning in Context Grading AI using AI |
OpenAI API sign-up |
| Week 3 | Generative AI and Private Knowledge Supervised Fine-tuning Retrieval-Augmented Generation Preference Optimization and Reinforcement Fine-tuning |
Project Groups |
| Week 4 | Reasoning Machines Test-time Scaling Laws Autonomous Tool-Use Agentic Systems |
Hands-on Agentic AI |
| Week 5 | Augmented Intelligence Diagnosing Decisions with AI Designing Human-Algorithm Collaborations Artificial Intelligence Alignment Performativity and Strategic Classification |
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| Week 6 | In-Class Midterm Exam Tests all material upto & including Week 5 Open notes, laptop, internet, ChatGPT, etc. allowed No human-human collaboration allowed |
Practice Exam |
| Spring Break | ||
| Week 7 | Project Hackathon Groups work with me in my office to implement their project demo Come with your idea and data! |
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| Week 8 | Recommendation Machines Factorizing Interaction Matrices The Cold-start Problem Missingness and Feedback Loops Case Study: Spotify |
Homework 2: Prompt Engineering |
| Week 9 | Causal Artificial Intelligence Causal Inference: The “What If” Problem Heterogeneous Treatment Effects Personalized Treatment Policies |
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| Week 10 | Unsupervised Artificial Intelligence Clustering and Consumer Segmentation Anomaly and Outlier Detection Dimensionality Reduction and Embeddings |
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| Week 11 | Explainable Artificial Intelligence Explainable Models vs. Post-hoc Interpretation LIME: Local Explanations Global Explanations via Shapley Values |
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| Week 12 | In-Class Project Presentations Virtual Focus Group (slides) TikTokified Exam Prep (slides) Job Recommender (slides) Uncovering Implicit Review Scores (slides) Liars and Thieves (slides) Evaluating Sportsperson Team Transfers (slides) Outfit Completion (slides) Reducing Package Returns (slides) Book Recommender (slides) Improving EV Charging (slides) Doing More with Fewer Hospital Beds (slides) Automating News Website Layouts (slides) |
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