AgentFlowAcademy

Track · For beginners & testers

Python for AI Work

Only the Python you need to read agent code, write tools and work with data. Watch every program run line by line.

Free 24 lessons · 6 modules · 24 live now

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Module 1 Getting started

  1. 01 Why AI runs on Python What Python is, why ML and agent frameworks chose it, and how to read your first program. Start →
  2. 02 Install, virtual environments and pip python, venv, pip and requirements.txt, so projects don't break each other. Start →
  3. 03 Variables, numbers and types Names, ints, floats, booleans, None and type conversion. Start →
  4. 04 Strings and f-strings Slicing, methods and formatting: the skills behind every prompt template. Start →

Module 2 Control and data

  1. 05 If, for and while Branches and loops, with break, continue and else. Start →
  2. 06 Lists and tuples Ordered data: indexing, slicing, mutation and when to use which. Start →
  3. 07 Dictionaries and sets Key-value data, the shape of every JSON payload and tool argument. Start →
  4. 08 Comprehensions Building lists, dicts and sets in one readable line. Start →

Module 3 Functions and modules

  1. 09 Functions Parameters, defaults, keyword arguments, return values and docstrings: exactly what ADK turns into tools. Start →
  2. 10 Lambda, map, filter and sorted Functions as values, and the key= pattern. Start →
  3. 11 Modules, packages and imports How import finds code, and how a project is laid out. Start →
  4. 12 Type hints Annotating functions so tools get the right schema and editors catch mistakes. Start →

Module 4 Objects

  1. 13 Classes and objects Attributes, methods, __init__ and self. Start →
  2. 14 Inheritance and composition Reusing behaviour, and when not to subclass. Start →
  3. 15 Dataclasses and Pydantic Typed data containers and validated models, the backbone of structured output. Start →

Module 5 Robust code

  1. 16 Exceptions try, except, else, finally, raising, and why tools should let errors propagate. Start →
  2. 17 Files, JSON and CSV Reading and writing data with context managers. Start →
  3. 18 Logging Levels, formats and why print() isn't enough in production. Start →
  4. 19 Testing with pytest Writing tests, fixtures and running them, the base for agent evals. Start →

Module 6 Advanced Python for AI work

  1. 20 Iterators and generators Lazy sequences and yield: how ADK streams events. Start →
  2. 21 Decorators and context managers Wrapping functions and managing resources. Start →
  3. 22 async and await Concurrency for I/O: why agent runners are async. Start →
  4. 23 NumPy and pandas basics Arrays, vectors and dataframes for embeddings and evaluation results. Start →
  5. 24 Calling APIs and keeping secrets HTTP requests, JSON responses, environment variables and .env files. Start →