Pick your stack
Can't decide which path to take? Explore the roles, responsibilities, and tools for each track before you commit.
How to use this page
This hub is built for the resourceful data professional. Whether you have a $0 budget or enterprise suite access, every resource listed here has a free or free-tier option. Pick your track below to see curated tools, certifications, datasets, and communities for that specific path.
Data Simplified for Beginners
The precise order of operations for a real data project — terminology, step-by-step workflow, common pitfalls, and annotated Python and PySpark code examples. Built for people who want to get it right the first time.
Pick Your Sector
The domain dictates the workflow, not just the tools. A data scientist in healthcare worries about patient privacy and life-or-death accuracy. One in finance worries about fraud and regulation. Explore how roles, terminology, stack, and ethics shift across 16 major sectors.
Build Your Data Stack from Zero
A complete guide to building a production-ready data engineering platform on free tiers. GitHub Actions, Cloudflare D1, S3, BigQuery, dbt, and more. Zero dollars, real production skills.
Data Science & Analytics
SQL, BI tools, statistical modelling, A/B testing, and domain-specific analytics for finance, healthcare, HR, and consumer sectors.
Machine Learning & AI
Foundation models, deep learning, NLP, computer vision, MLOps, and GenAI development across real-world sectors.
Data Engineering
ETL/ELT pipelines, orchestration, cloud data warehouses, streaming, data quality, and the modern data stack from ingestion to serving.
Computer Science
Algorithms, data structures, databases (SQL, NoSQL, graph, vector), system design, APIs, and full-stack engineering fundamentals.