Advanced Lessons

Session 1, Part 2: Market Identification and Sales: Finding Your Customer

Session 25: Anthropogenic CO2 (2) and Review

Lec 23. Metrized Deep Learning

Lecture 03: Externalities in Theory & Practice

Lecture 05: Public Goods Theory, Optimality, and Pricing

Lecture 02: Externalities in Theory

Lecture 10: Social Insurance Theory

3: Deep Learning for Computer Vision – Building Convolutional Neural Networks from Scratch

10: Generative AI – Adapting LLMs with Parameter-Efficient Fine-Tuning

Lecture 7: Generating Functions for Catalan Numbers

Lecture 3: Inclusion-Exclusion

Lecture 17: Huffman Coding

Lecture 11: Basic Group Theory

Lecture 13: Duality in Linear Programming

Lecture 15: Max-Flow Min-Cut Theorem

Lecture 2: Independence and Conditioning

Lecture 8: Tail Bounds

Lecture 4: Counting

Lecture 2: Linear Algebra

Lecture 5: Probability Theory (cont.); Stochastic Processes I

Lecture 25: Stochastic Calculus (cont.); Stochastic Differential Equations

Lecture 09: Reflections on the Szemeredi-Trotter Theorem

Lecture 19: Random Walks on Finite Groups, Part 3

Lecture 18: Random Walks on Finite Groups, Part 2