Career paths
Each path is a dependency-ordered skill roadmap, not a promise. Coverage percentages elsewhere in the app are learning-readiness estimates, never a hiring probability.
Software Engineer
General-purpose backend/full-stack engineering foundations.
Stages: Foundation → CS Fundamentals → Engineering → Systems → Interview Prep
View roadmapFull-Stack Engineer
Frontend + backend, from HTML to a deployed API.
Stages: Foundation → Frontend → Backend → CS Fundamentals → Engineering
View roadmapBackend Engineer
APIs, databases, and the systems that keep them reliable.
Stages: Foundation → CS Fundamentals → Data → Engineering → Systems
View roadmapData Engineer
Pipelines, warehouses, and moving data reliably at scale.
Stages: Foundation → Data Modeling → Pipelines → Engineering → Math
View roadmapData Scientist
Statistics, experimentation, and applied ML on real data.
Stages: Foundation → Data → Math → ML → Projects
View roadmapML Engineer
Building, training, and shipping ML models in production.
Stages: Foundation → Data → Math → ML Core → Deployment
View roadmapAI Engineer
Applied LLM/AI systems — RAG, agents, embeddings, evaluation.
Stages: Foundation → AI Core → Applied → Engineering → Math
View roadmapQuant Developer
Low-latency systems and infrastructure for trading strategies.
Stages: Foundation → Math → Algorithms → Quant → Engineering
View roadmapQuant Researcher
Statistical research, factor models, and strategy backtesting.
Stages: Foundation → Math → Quant → Data → Projects
View roadmapQuant Trader
Markets, risk, and systematic strategy intuition.
Stages: Foundation → Math → Markets → Quant → Data
View roadmapResearch Engineer
Systems + ML research — bridging papers and production code.
Stages: Foundation → CS Fundamentals → Math → ML → Systems
View roadmap