Getting Started
New to tech economics? This curated guide helps you focus on what matters most. Pick a path below based on your goals.
Learning Paths
Choose a roadmap based on what you want to learn. Each includes recommended resources and packages to get started.
Learn Python
Programming fundamentals for economists — data manipulation, visualization, and workflows
Resources
- Coding for Economists Built specifically for econ researchers
- The Missing Semester (MIT) Git, shell, debugging — skills they don't teach in PhD programs
- Python for Econometrics NumPy, pandas, statsmodels from Kevin Sheppard
- Python Data Science Handbook Free reference for NumPy, Pandas, Matplotlib
Packages
- pandas Data manipulation and analysis
- numpy Numerical computing foundation
- matplotlib Basic visualization
- jupyter Interactive notebooks for exploration
Learn Statistics
Hypothesis testing, inference, and distributions — the foundation for empirical work
Resources
- StatQuest (Josh Starmer) Visual intuition for stats — the 'Bill Nye of Statistics'
- Seeing Theory (Brown) Beautiful interactive visualizations for building intuition
- Think Stats Programming-first approach with real datasets
- Scipy.stats Documentation Reference for distributions and tests
Packages
- scipy Statistical functions and distributions
- statsmodels OLS, GLM, and classical econometrics
- pingouin ANOVA, t-tests, and correlations made easy
- lifelines Survival analysis and hazard models
Learn ML
Prediction, tree models, and cross-validation — for forecasting and pattern recognition
Resources
- Introduction to Statistical Learning Free, runnable Python code, intuition first
- Google ML Crash Course 130+ interactive exercises, refreshed 2024
- Hands-On Machine Learning (Géron) Production-focused, complements ISLR's statistical focus
- fast.ai Practical Deep Learning Code first, theory second
- Andrew Ng's ML Specialization The classic introduction, rebuilt 2022 with Python
- Andrew Ng's Deep Learning Specialization CNNs, RNNs, and transformers from the master
Packages
- scikit-learn The go-to library for classical ML
- XGBoost Gradient boosting for tabular data
- LightGBM Fast gradient boosting from Microsoft
- CatBoost Handles categorical features natively
Learn Causal Inference
Treatment effects, DiD, RDD, and IV — answer 'what if' questions with data
Resources
- Causal Inference for the Brave and True The best free intro with Python code
- The Effect DAGs that don't suck, readable and modern
- Causal Inference: The Mixtape Reads like a conversation, not a textbook
Learn Product Sense
Metrics, experimentation, and business thinking — bridge economics and product decisions
Resources
- Trustworthy Online Controlled Experiments (Kohavi) THE definitive book — praised by Jeff Dean and Adam D'Angelo
- Eppo's Experimentation Guides Practical, written by practitioners
- GrowthBook Documentation Free, open-source, structured learning path
- Evan Miller: How Not To Run an A/B Test Short, lethal, career-saving
- Netflix Tech Blog - Experimentation Real case studies at scale
Packages
- Spotify Confidence Production-grade A/B testing
- GrowthBook SDK Feature flags and experiments
- Ax Meta's adaptive experimentation platform
Learn SQL
Querying data, joins, and aggregations — essential for any data role
Resources
- SQLBolt No setup, run queries in browser — start here
- Mode SQL Tutorial Interactive lessons with real database
- SELECT Star SQL Interactive book teaching SQL through meaningful analysis
- 8 Week SQL Challenge (Danny Ma) 8 business case studies with CTEs and window functions
- DataLemur Real DS interview questions with business context
Packages
- duckdb Modern SQL on your laptop, reads Parquet
- sqlalchemy Python's database toolkit
- pandasql SQL syntax on pandas DataFrames
Learn LeetCode
Data structures and algorithms for coding interviews — learn foundations first, then grind
Resources
- Structy Designed for true beginners, progressive difficulty ($60/yr)
- Abdul Bari (YouTube) Exceptional whiteboard DSA explanations
- NeetCode Curated roadmap with video explanations
- Blind 75 / Grind 75 The 75 problems you need to master
- LeetCode Patterns 14 patterns to solve any question
Learn Automation
Web scraping, APIs, and workflow automation — collect and process data at scale
Resources
- Automate the Boring Stuff with Python Free, practical skills for data work
- Postman Academy Free API certification path — often more useful than scraping
- Real Python: Web Scraping BeautifulSoup and requests guide
- Playwright for Python Modern browser automation (faster than Selenium)
- Scrapy Documentation Industrial-strength web scraping
Packages
- requests HTTP for humans — start here
- beautifulsoup4 Parse HTML the simple way
- playwright Modern browser automation from Microsoft
- scrapy Production web scraping framework
Learn Optimization (OR)
Linear programming, convex optimization, and combinatorial methods — solve pricing, scheduling, and allocation problems
Resources
- Convex Optimization (Boyd & Vandenberghe) The bible — free online, universally cited
- Stanford EE364A (YouTube) Boyd's legendary lectures — the gold standard
- Discrete Optimization (Coursera) Van Hentenryck's course — actually makes you implement
- CVXPY Short Course Hands-on convex optimization in Python
Packages
- cvxpy Write math as code — the standard for convex problems
- scipy.optimize Built into SciPy — start here for basics
- OR-Tools Google's production-ready combinatorial optimization
- Gurobi Best-in-class solver — free for academics
Learn Agentic Workflows
Build AI agents that reason, plan, and execute — tool use, multi-agent systems, and orchestration
Resources
- Agentic AI (DeepLearning.AI) Andrew Ng on the four design patterns — start here
- AI Agents in LangGraph (DeepLearning.AI) Build agents from scratch with Harrison Chase
- Building Effective Agents (Anthropic) Design patterns from Claude's creators — best practitioner guide
- LangGraph Documentation Official docs — the industry standard framework
Packages
- langgraph Graph-based agent workflows — production standard
- langchain LLM framework — chains, tools, memory
- crewai Role-based multi-agent teams — intuitive orchestration
- openai-agents OpenAI's lightweight SDK — fast prototyping
Explore the Full Database
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