Lecture 08: Local Public Goods and Fiscal Federalism

Lecture 04: Externalities in Practice II

Lecture 15: Health Care III, Redistribution

Lecture 14: Health Care II

Lecture 11: Social Security

Lecture 07: Political Economy

Lecture 03: Externalities in Theory & Practice

Lecture 05: Public Goods Theory, Optimality, and Pricing

Lecture 22: Wealth Taxation

Lecture 17: Redistribution and Welfare, Taxation Overview

Lecture 02: Externalities in Theory

Lecture 18: Overview of Taxation and Tax Base, Tax Incidence

Lecture 10: Social Insurance Theory

Lecture 24: Corporate Taxation and Tax Reform

Lecture 06: Cost/Benefit Analysis

Lecture 19: Tax Incidence and Tax Efficiency

Lecture 13: Health Care I

Lecture 21: Taxation and Savings

Lecture 01: Why Study Public Finance?

Lecture 23: Corporate Taxation

Lecture 16: Redistribution and Welfare Policy

Lecture 12: Other Social Insurance Programs

Lecture 09: Public Provision of Private Goods: Education

Lecture 20: Taxation and Labor Supply

S7SE Special Episode: Collaborating with Community Colleges

MIT Economist Jon Gruber responds to YouTube comments

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

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

8: Deep Learning for Natural Language – Transformers, Self-Supervised Learning

9: Generative AI – Large Language Models (LLMs) and Retrieval Augmented Generation (RAG)

5: Deep Learning for Natural Language – The Basics

2: Training Deep NNs (cont.); Introduction to Keras/Tensorflow; Application to Tabular Data

4: Deep Learning for Computer Vision – Transfer Learning and Fine-Tuning; Intro to HuggingFace

6: Deep Learning for Natural Language – Embeddings

7: Deep Learning for Natural Language – Transformers

11: Generative AI – Text-to-Image Models

1: Introduction to Neural Networks and Deep Learning; Training Deep NNs

Lecture 16: Data Compression and Shannon’s Noiseless Coding Theorem

Lecture 7: Generating Functions for Catalan Numbers

Lecture 3: Inclusion-Exclusion

Lecture 17: Huffman Coding

Lecture 11: Basic Group Theory

Lecture 20: Reed-Solomon Codes

Lecture 9: Chernoff Bounds

Lecture 13: Duality in Linear Programming

Lecture 18: Transmitting Information Reliably over a Noisy Channel & Shannon’s Noisy Coding Theorem

Lecture 14: Zero-Sum Games

Lecture 15: Max-Flow Min-Cut Theorem

Lecture 2: Independence and Conditioning

Lecture 5: More Counting and Generating Functions

Lecture 6: More on Generating Functions

Lecture 8: Tail Bounds

Lecture 19: Error-Correcting Codes—Hamming Codes

Lecture 10: Modular Arithmetic

Lecture 12: Introduction to Linear Programming

Lecture 1: Pigeonhole Principle

Lecture 4: Counting

“Learning for Life: How Curiosity Shapes Well-Being” with Bia Adams

Lecture 20: Building the First Federally (CFTC) Regulated Exchange Dedicated to Trading on Events

Lecture 1, Part III: Bond “Mathematics”