Learning paths
Real subjects from the actual product — not a generic list.
Every path is a sequence of nodes. Each node is Learn → Simulate → Quiz. Open any track to see the same chrome students use after they log in.
Data Structures & Algorithms
Fixed-size, index-addressed memory — the base every other structure builds on. Then trees, graphs, DP, and the patterns companies actually ask.
18 nodes · 42 hrs · +1420 XP
SQL
The language every backend, data, and analytics interview still opens with. Joins, windows, and query plans — not just SELECT *.
14 nodes · 18 hrs · +880 XP
Git & GitHub
The difference between a student project and something a team can ship. Branching, PRs, rebase, and the incidents you'll cause if you skip this.
10 nodes · 8 hrs · +420 XP
Python
The language of interviews, scripting, data, and a surprising amount of backend. Idiomatic Python — not just the syntax your lab used.
16 nodes · 24 hrs · +960 XP
REST API & Backend Engineering
Auth, pagination, idempotency, and the 14 ways a naive CRUD API fails in production. The track job posts actually filter on.
16 nodes · 28 hrs · +1180 XP
System Design
Capacity, trade-offs, and the diagrams that get you past the 'design Instagram' round — taught as decisions, not decorations.
12 nodes · 20 hrs · +1040 XP
Cloud & DevOps
AWS, Azure, CI/CD, containers, and the ops instincts that keep a service up after you merge.
14 nodes · 22 hrs · +980 XP
React
Components, state, effects, and the performance instincts that keep a UI honest. The library most product teams still hire for.
14 nodes · 20 hrs · +920 XP
AI/ML Fundamentals
The math you actually need, the models companies fine-tune, and the evaluation that stops you shipping a confident wrong answer.
16 nodes · 30 hrs · +1260 XP
MLOps & Production ML
Training is the easy part. This track is everything after: versioning, serving, drift, and the on-call for a model.
12 nodes · 18 hrs · +890 XP
Landing next on PreCompilers
4 in the pipelineIn active build. XP, node counts and simulators lock in closer to release — the track names and scope are final.
AI Agents
Tool-calling, memory, planning loops and multi-agent orchestration — building software that takes actions, not just answers.
Gen AI
Prompting, RAG, fine-tuning and the eval discipline behind every 'we added AI to the product' feature.
QA & Testing
Test pyramids, flaky-test triage and the coverage discipline that stops 'it worked on my machine' from reaching prod.
Playwright
Browser automation that doesn't flake: selectors, network mocking, visual diffs, and CI runs across every browser engine.