Foundation of Economics Science (for Computer Scientists)

Course Outline:

1. Understanding Individual Choices using Machine Learning
2. Data as a Good
3. Taxation in the Age of Information Technologies
4. Growth and Innovation
5. Discrimination and AI Bias
6. Networks and Social Media
7. Blockchain & Bitcoin

Politics and Economics

Course Outline:

1. Interpersonal Utility Comparison
2. Politics/Politicians/Ideology
3. Lobbying
4. Efficiency: Behaviroul Biases and Addiction
5. Efficiency: Market Power
6. Efficiency: Negative Externalities
7. Equality: Theories of Justice
8. Equality: Social Insurance
9. Equality: Discrimination
10. Conflict
11. Social Media

Machine Learning Applications in Economics

Course Outline:

1. Introduction Machine Learning and Economics
2. A Short Introduction to Natural Language Processing
3. Applications of Supervised Machine Learning
   • Demand Estimation
   • Measuring Racial and Gender Biases Word Embeddings
   • Measuring Visual Bias using Image Classification
4. Applications of Unsupervised Machine Learning
   • Measuring Ideology using Clustering
   • Measuring Knowledge Transfers with LSA
   • Measuring Central Bank Communication using LDA

Machine Learning Reading Group

Reading Group Outline:

1. Text as Data
2. Supervised Machine Learning
3. Supervised Machine Learning Classifiers
4. Causal Machine Learning
5. Unsupervised Machine Learning
6. Topic Models

A Primer in Social Media Research

Lecture Outline:

1. Why Social Media Research is Relevant
2. How to Collect Social Media Data
3. Using Machine Learning for Social Media Research
4. Examples of Social Media Research