Career routes 6 role-based routes, each with a certificate
Phase 0
Setup and tooling
Get your environment ready for everything that follows.
12 lessons about 7.5 hFree
Your progress0 of 12
- 1Dev EnvironmentYour tools shape your thinking. Set them up once, set them up right.
- 2Git & CollaborationVersion control is not optional. Every experiment, every model, every lesson you build here gets tracked.
- 3GPU Setup & CloudTraining on CPU is fine for learning. Training for real needs a GPU.
- 4APIs & KeysEvery AI API works the same way: send a request, get a response. The details change, the pattern doesn't.
- 5Jupyter NotebooksNotebooks are the lab bench of AI engineering. You prototype here, then move what works into production.
- 6Python EnvironmentsDependency hell is real. Virtual environments are the cure.
- 7Docker for AIContainers make "works on my machine" a thing of the past.
- 8Editor SetupYour editor is your co-pilot. Configure it once so it stays out of your way and starts pulling its weight.
- 9Data ManagementData is the fuel. How you manage it determines how fast you go.
- 10Terminal & ShellThe terminal is where AI engineers live. Get comfortable here.
- 11Linux for AIMost AI runs on Linux. You need to know enough to not be stuck.
- 12Debugging and ProfilingThe worst AI bugs don't crash. They train silently on garbage and report a beautiful loss curve.
Phase 0 projects
Build these to prove you can use what this phase taught. Each is reviewed by Professor Katalock against its rubric, and passing them is required for the Phase 0 certificate. 0 of 2 passed.
Phase projectReproducible Dataset WorkspaceBuild a version-controlled Python project that fetches a public dataset, verifies it, converts it to Parquet and makes seeded splits that a fresh clone reproduces bit for bit.Phase projectInstrumented LLM Batch CLIBuild a command-line tool that sends a batch of prompts to any OpenAI-compatible endpoint over raw HTTP, keeps keys out of code, retries sensibly, logs every call and profiles where the time goes.
Final exam and Katalock certificate
20 questions, 30 minutes, pass mark 70%. Pass to earn a certificate with its own verifiable ID. Opens after this phase's 2 projects (0 of 2 passed).
Katalock AI Engineering curriculum. How the Academy works. Career routes. Certification prep. Verify a certificate.