Giulia Caprini

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Giulia Caprini

Assistant Professor of Economics

giulia(dot)caprini[squiggly a]sciencespo.fr

Department of Economics

Sciences Po, Paris

Teaching

Below is a list of courses I currently teach and have taught in the past.

Sciences Po Sciences Po, Paris

Computer Programming for Economics Research

Spring 2026 · School of Economics, Sciences Po

This course teaches programming skills essential for modern economics research, covering data analysis, computational methods, and reproducible research practices.

View Course Structure (Two Parts)
Part 1: ProTools ER1 (M1 Course)

This first part, designed for M1 students, focuses on the foundational programming skills most needed for empirical research:

  • Programming foundations: Python, Stata, and R taught in parallel — data import, cleaning, exploration, and visualization
  • Causal inference methods: Matching, Difference-in-Differences, Regression Discontinuity, Instrumental Variables, Synthetic Control
  • Estimation techniques: Standard errors, panel data methods, MLE/GMM
  • Research best practices: Version control with Git & GitHub, replicability standards, project organization
  • Machine learning & NLP: Introduction to ML for economists, history of NLP, understanding Large Language Models

Access course materials here. Note: for Spring 2026, access is restricted to enrolled students only.

Part 2: ProTools ER2 (M2 Course — Coming Soon)

The second part, designed for M2 students, focuses on AI tools and cutting-edge skills for modern research:

  • Image & text analysis with LLMs: Extracting structured data from documents, PDFs, and images using AI
  • Local LLM deployment: Setting up LM Studio, running open-source models locally on your machine
  • AI coding assistants: Using Claude Code from Claude Desktop and VS Code for research workflows
  • Hugging Face ecosystem: Accessing models, datasets, and Spaces for research applications
  • API & inference services: Buying credits, managing API keys, choosing between providers (OpenAI, Anthropic, etc.)
  • Building AI-powered tools: Research websites, data dashboards, and automated pipelines
  • Prompt engineering: Advanced techniques for getting reliable outputs from LLMs
  • RAG & fine-tuning: Retrieval-augmented generation and model customization for domain-specific tasks

Link to Part 2 will be provided when available.

The Economics of Digital Platforms and Social Media

Fall 2025 · School of Public Affairs, Sciences Po

This course examines the economic principles underlying digital platforms and social media, including network effects, data economics, and market structure.

Oxford University Oxford University

Quantitative Methods 1 (Econometrics) [Graduate]

Fall 2024 · Nuffield College, Oxford

Quantitative Methods 1 (Econometrics) [Graduate]

Fall 2023 · Nuffield College, Oxford

Computer Programming for Quantitative Methods 1 (Econometrics) [Graduate]

Fall 2022 · Nuffield College, Oxford

Computer Programming for Quantitative Methods 2 (Adv. Econometrics) [Graduate]

Fall 2022 · Nuffield College, Oxford

NYU NYU Florence

TA for Econometrics [Undergraduate]

Fall 2019 · Instructor: Prof. Giampiero Gallo