Weekly Content

Week00: AI for coding

Using AI for code. May not be covered in this class, as it had often been already covered in coding classes.

Week01: LLM Review

What are LLMs, how is the magic happening. A non-technical brief intro. How to work with LLMs? Plus ideas on applications. Includes suggested readings, podcasts, and vids to listen to.

Content

Which AI? See my take on current models. As of May 2025.

Week02: Data and code discovery and documentation with AI

Learn how to write a clear and professional code and data documentation. LLMs are great help once you know the basics.

Case study: World Values Survey

Content

Week 03: Writing Reports

You have your data and task, and need to write a short report. We compare different options with LLM, from one-shot prompt to iteration.

Case study: World Values Survey

Content

Week04: Agentic AI with Claude Code

From chat to terminal - introducing Claude Code for data analysis. Students learn to use agentic AI that works directly with files, generates data, and iterates on analysis.

Case study: Austrian Hotels

Content

Week05: Advanced CLI Workflows

Going deeper with CLI tools: custom skills, project-specific instructions (CLAUDE.md), git integration, and autonomous execution.

Content

Week06: From Data to Report

Download real CPS earnings data via CLI, contrast an undirected “vibe report” with a carefully directed economics-quality report. Iterative graph refinement, OLS regressions, and constrained PDF output.

Case study: US Earnings (CPS)

Content

Week07: Text as data 1 – intro lecture

No course of mine can escape football (soccer). Here we look at post-game interviews to learn basics of text analysis and apply LLMs in what they are best - context dependent learning. Two class series. First is more intro to natural language processing.

Case study: Football Manager Interviews

Content

Week08: Sentiment Analysis with AI

Second class, now we are in action. How does LLM compare to humans?

Case study: Football Manager Interviews

Content

Week09: AI as research companion: Control variables

Content

Week10: AI as research companion: Instrumental variables

Content

Week11: AI as research companion: Differences in differences

TBA

Week12: Creating simulations with apps and dashboards

Content

TBA

--- title: "Weekly Content" --- ### Week00: AI for coding Using AI for code. May not be covered in this class, as it had often been already covered in coding classes. [Content](../week00) ## Week01: LLM Review What are LLMs, how is the magic happening. A non-technical brief intro. How to work with LLMs? Plus ideas on applications. Includes suggested readings, podcasts, and vids to listen to. [Content](../week01/) **Which AI?** See [my take on current models](../da-knowledge/which-ai.html). As of *May 2025*. ## Week02: Data and code discovery and documentation with AI Learn how to write a clear and professional code and data documentation. LLMs are great help once you know the basics. Case study: [World Values Survey](../case-studies/VWS/) [Content](../week02/) ## Week 03: Writing Reports You have your data and task, and need to write a short report. We compare different options with LLM, from one-shot prompt to iteration. Case study: [World Values Survey](../case-studies/VWS/) [Content](../week03/) ## Week04: Agentic AI with Claude Code From chat to terminal - introducing Claude Code for data analysis. Students learn to use agentic AI that works directly with files, generates data, and iterates on analysis. Case study: [Austrian Hotels](../case-studies/austria-hotels/) [Content](../week04/) ## Week05: Advanced CLI Workflows Going deeper with CLI tools: custom skills, project-specific instructions (CLAUDE.md), git integration, and autonomous execution. [Content](../week05/) ## Week06: From Data to Report Download real CPS earnings data via CLI, contrast an undirected "vibe report" with a carefully directed economics-quality report. Iterative graph refinement, OLS regressions, and constrained PDF output. Case study: [US Earnings (CPS)](../case-studies/earnings/) [Content](../week06/) ## Week07: Text as data 1 -- intro lecture No course of mine can escape football (soccer). Here we look at post-game interviews to learn basics of text analysis and apply LLMs in what they are best - context dependent learning. Two class series. First is more intro to natural language processing. Case study: [Football Manager Interviews](../case-studies/interviews/) [Content](../week07/) ## Week08: Sentiment Analysis with AI Second class, now we are in action. How does LLM compare to humans? Case study: [Football Manager Interviews](../case-studies/interviews/) [Content](../week08/) ## Week09: AI as research companion: Control variables [Content](../week09/) ## Week10: AI as research companion: Instrumental variables [Content](../week10/) ## Week11: AI as research companion: Differences in differences TBA ## Week12: Creating simulations with apps and dashboards [Content](../week12/) TBA