InterviewsVector
Original Academy

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Setup & Tooling

Get your environment ready for everything that follows.

Provenance: this phase outline and its lesson readings are preserved from ai-engineering-from-scratch by Rohit Ghumare under the MIT License. InterviewsVector does not claim authorship. These archive pages remain available for old links and progress, but are excluded from indexing.

Attributed readings

  1. 01Dev EnvironmentYour tools shape your thinking. Set them up once, set them up right.
  2. 02Git & CollaborationVersion control is not optional. Every experiment, every model, every lesson you build here gets tracked.
  3. 03GPU Setup & CloudTraining on CPU is fine for learning. Training for real needs a GPU.
  4. 04APIs & KeysEvery AI API works the same way: send a request, get a response. The details change, the pattern doesn't.
  5. 05Jupyter NotebooksNotebooks are the lab bench of AI engineering. You prototype here, then move what works into production.
  6. 06Python EnvironmentsDependency hell is real. Virtual environments are the cure.
  7. 07Docker for AIContainers make "works on my machine" a thing of the past.
  8. 08Editor SetupYour editor is your co-pilot. Configure it once so it stays out of your way and starts pulling its weight.
  9. 09Data ManagementData is the fuel. How you manage it determines how fast you go.
  10. 10Terminal & ShellThe terminal is where AI engineers live. Get comfortable here.
  11. 11Linux for AIMost AI runs on Linux. You need to know enough to not be stuck.
  12. 12Debugging & ProfilingThe worst AI bugs don't crash. They train silently on garbage and report a beautiful loss curve.