Tutorials & Practice¶

Free, high quality¶

• Kaggle Learn — short, hands-on tracks (Pandas, SQL, ML, Visualization)
• StatQuest YouTube — best stats explanations on the internet
• 3Blue1Brown — visual math (linear algebra, probability)
• Seeing Theory — interactive probability/stats
• Computerphile — computing concepts explained

Topical learning¶

Database Administrator¶

• Fundamentals of Database Administration - By Brent Ozar
• SmartPostgres - By Brent Ozar but focus on PostgreSQL
• Decomplexify - Explain complex simply
• Ben Dicken - Databases, distributed systems, software engineering

Data Engineering¶

• Data Engineer Bootcamp FREE 27+ Hour Course - SQL, Python, Cloud, Bash, AI, Git & GitHub

Python¶

• Real Python — pandas
• Guide to NumPy, pandas, and Data Visualization

SQL¶

• PostgreSQL Tutorial
• Use The Index, Luke — SQL performance

Visualization¶

• Tableau Public training
• From Data to Viz — chart selection
• Storytelling with Data podcast

Statistics¶

• StatQuest — Statistics fundamentals

Communication¶

• Storytelling with Data — Cole Knaflic blog

Blockchain / Web3¶

• Crypto Data Analyst Roadmap (roadmap.sh)
• Basic Wizard Guide to Dune SQL — SQL for Ethereum data analytics
• Understanding Transactions, Traces, and Logs — reading block explorers and onchain data structures

Practice platforms¶

• Stratascratch — interview-style problems
• LeetCode — SQL
• HackerRank — SQL
• DataLemur — analytics interview SQL
• Kaggle Competitions
• DataCamp Projects
• SQL Noir — SQL puzzle games
• SQL Zoo — SQL basics practice

Portfolio Evaluation Checklist¶

- [ ] Anything missing? Steps in projects? Details in descriptions?
- [ ] If you have a website, are all pages accounted for?
- [ ] If hosted on a platform, are projects uploaded properly?
- [ ] Is there too much info?
- [ ] Could descriptions be revised for brevity?
- [ ] Places where you include more data than needed? Could anything be cut without losing meaning?
- [ ] Anything you shouldn't include?
- [ ] Have you included references to others' work without citing them? Replace with links.
- [ ] Anything seem extraneous or unprofessional?
- [ ] Is portfolio hosted on the most appropriate platform?
- [ ] Considered options: GitHub, Kaggle, Tableau Public, personal site

Interview Prep¶

• Neetcode — tech interview prep

Certifications¶

• Google Data Analytics Certificate (Coursera) — beginner, free with audit
• Google Advanced Data Analytics Certificate — intermediate; Python, ML
• Tableau Desktop Specialist
• Microsoft DA Associate (PL-300)
• AWS Data Analytics Specialty
• GCP Professional Data Engineer