Structured Learning Paths
Programs built around the courses already shipping now, plus a professional engineering pathway that is being assembled in the same practical, production-first format.
Ready now
Programs You Can Start Today
Ready Nowbeginner
Applied Data Foundations
A practical start for learners who want coding, SQL, and analytical confidence before moving into machine learning or engineering tracks.
8-10 weeks 3 courses Project-based delivery
Career outcomes
Junior Data AnalystData Science TraineeTechnical Research Assistant
Current curriculum
- 1Python for Data Science
- 2SQL for Data Science
- 3Statistics & A/B Testing for Data Science
Ready Nowintermediate
AI Engineering Track
A production-minded AI path combining core Python, modern AI application engineering, and experimental decision systems.
10-12 weeks 3 courses Project-based delivery
Career outcomes
AI EngineerLLM Application EngineerApplied ML Engineer
Current curriculum
- 1Python for Data Science
- 2SQL for Data Science
- 3AI Engineering
Ready Nowbeginner
Data Engineering Track
A hands-on data workflow track focused on tooling, engineering habits, and production pipeline thinking.
8-10 weeks 3 courses Project-based delivery
Career outcomes
Junior Data EngineerAnalytics EngineerPlatform Operations Associate
Current curriculum
- 1VS Code + WSL Beginner Workflow
- 2SQL for Data Science
- 3Data Engineering
In Developmentintermediate
Professional Engineering Pathway
A full professional engineering pathway for learners who want to move from local developer workflow to production infrastructure, reliability, and operational readiness.
6-9 months 13 planned courses Built from real engineering workflows
Target roles
Platform EngineerMLOps EngineerDevOps EngineerCloud Infrastructure Engineer
By the end you'll be able to
Ship containerized apps to production Kubernetes
Build CI/CD pipelines from commit to deploy
Stand up observability — logs, metrics, tracing
Architect cloud infrastructure as code
Run resilient distributed systems with real SLOs
Pathway build-out
Stage 1: Engineering Foundations
Linux & WSL engineering
Python project engineering
Git & GitHub workflows
Environments & dependency systems
Stage 2: Build & Ship
Docker
CI/CD
Kubernetes
Stage 3: Operate & Scale
Observability & SRE
Platform security
Cloud architecture
Stage 4: Advanced Production Systems
Distributed systems
Resilience engineering
Final production operations