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All tracks start the same way

Every learner starts with Foundation — 6 shared modules covering Python, SQL, Pandas, Statistics, Git, and intro ML. You don’t need to lock in your track decision on day one. The Foundation curriculum is identical regardless of which track you choose. Your career track unlocks after Foundation is complete (~7 weeks in).

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Track comparison

AI EngineerData ScientistML EngineerData Engineer
Best forBuilding AI productsRunning experimentsTraining modelsBuilding pipelines
Duration~22 weeks~20 weeks~22 weeks~20 weeks
Core toolsClaude, LangChain, pgvectorscikit-learn, statsmodelsPyTorch, BentoMLdbt, Spark, Kafka
CapstoneAI productKaggle competitionML systemData platform
Hiring outlook🔥 Very high demand✅ Strong demand✅ Strong demand✅ Strong demand

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Which track is right for you?

  • You want to build products powered by LLMs
  • You’re excited about RAG, agents, and prompt engineering
  • You come from a software engineering background
  • You want to work at AI-native companies or build your own AI product
You’ll build: RAG pipelines, Claude-powered agents, LLM evaluation systems, and a complete AI product for your capstone.
  • You want to run experiments and build models that drive decisions
  • You’re comfortable with statistics and want to go deeper
  • You come from an analytics or research background
  • You want to work at product companies running A/B tests and ML models
You’ll build: Statistical models, A/B test analyses, feature engineering pipelines, and a Kaggle-style competition for your capstone.
  • You want to train and deploy models at scale
  • You’re interested in deep learning and production ML systems
  • You come from a software or data engineering background
  • You want to work at companies with serious ML infrastructure
You’ll build: PyTorch training loops, distributed training setups, model serving APIs, and a production ML system for your capstone.
  • You want to build the infrastructure that powers data teams
  • You’re interested in pipelines, warehouses, and streaming systems
  • You come from a software engineering or analytics background
  • You want to work at data-driven companies building modern data stacks
You’ll build: dbt projects, Spark pipelines, Kafka streaming systems, and a complete data platform for your capstone.

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Can I switch tracks later?

Yes. You can change your selected track from your account settings. Your Foundation progress carries over automatically. Any career track progress you’ve made on your previous track is saved — if you switch back, you pick up where you left off.
Switching tracks resets your cohort matching. You’ll be re-matched with a new cohort on the following Sunday’s matching run.