AI Applications in Business:
Insights from Corporate Data
Undergraduate & MBA · Instructor: Miao Liu
Machine Learning Unit
Introduces the core supervised learning framework — prediction, overfitting, regularization, decision trees, ensemble methods, neural networks and deep learning. Students apply these tools to real business datasets, building intuition for when and why ML outperforms traditional statistical approaches in accounting and finance contexts.
Large Language Models Unit
Covers the transformer architecture, attention mechanisms, and the emergence of large language models. Students learn to apply LLMs to corporate text data — earnings calls, analyst reports, and social media — exploring both the capabilities and limitations of AI-generated language in business and financial contexts.
Valuation Unit
This unit teaches financial accounting and corporate valuation with LLMs as a genuine co-pilot, embedded at every stage of the analytical process. Students master the fundamentals of reading financial statements, forecasting cash flows, and building DCF models, while developing a rigorous meta-prompting discipline: a systematic approach to designing prompt sequences that instruct an LLM to retrieve relevant data from public filings, reconcile accounting line items, stress-test assumptions, and produce well-documented valuation outputs. What makes this unit distinctive is its conviction that rigor and AI assistance are complements, not substitutes, and students leave with both the accounting intuition to challenge a model's output and the prompting fluency to make that model maximally useful.
Vibe Coding Unit
An emerging unit on AI-assisted programming — using large language models as coding collaborators to build, prototype, and analyze business applications without traditional software engineering expertise.
Materials coming soon.