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Python and Fast API

Full beginner-to-practice Python path for AI engineers: taught in syllabus order—from setup and syntax through numbers, collections, iterators, advanced functions, files and errors, object-oriented patterns, typing, the standard library, HTTP/FastAPI serving, concurrency, pytest, and packaging. Lessons use detailed explanations plus runnable in-browser examples.

Beginner 36 hours · Self-paced 99.0 USD · 49 lessons · ~499 min read

15 topics 49 lessons Start anywhere
Grounded in sources, not a frozen script Ideas in this path map to readings and the Research Lab. See how we refresh lessons as the field moves.

What you’ll get out of this course

  • Build practical skill in “Python and Fast API” with text-first lessons and clear checkpoints.
  • Level: Beginner—follow the syllabus in order or jump to the modules you need.
  • Reinforce ideas with end-of-topic checks and (where available) hands-on coding tasks.

Trust & quality

Content is designed and maintained by the Deep AI Minds team—structured for working adults, with frequent updates as tooling and best practices evolve.

Content currency: ~100% of lessons on the current curriculum revision

Instructor & outcomes

Deep AI Minds

Curriculum & instruction

Structured, industry-relevant paths with clear checkpoints and refresh cadence.

Satisfaction & billing

30-day satisfaction: if the syllabus or access is not as described, contact support and we will help (refunds for eligible purchases, case by case for integrations).

Common questions

You keep access for the lifetime of the catalog item you purchased, subject to fair use and our terms.

Yes—add your company name at checkout (where available) or contact us for team licensing and PO-based billing.

Review the full syllabus before buying. If something is wrong on our side, reach out and we will make it right.
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Syllabus

We structured this course to build your skills step by step

Scroll through each module below—open lessons in place or jump into a topic. Everything runs in order, but you’re free to explore.

Topic 2
Learning module

Python essentials

The small set of language ideas you will use every day in AI work.

Variables and types 14 min
Control flow 13 min
Functions and modules 14 min
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Topic 3
Learning module

Numbers and operators

Integers, floats, math helpers, and precision pitfalls you will hit in real ML code.

Integers and floats 7 min
Arithmetic and the math module 7 min
Precision, rounding, and money 8 min
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Topic 4
Learning module

Collections deep dive

Lists, tuples, sets, dicts, and comprehensions — the daily working set for any Python programmer.

Lists in detail 8 min
Tuples and sets 7 min
Dictionaries in detail 9 min
Comprehensions, mastered 8 min
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Topic 6
Learning module

Iterators and generators

Lazy sequences, the iterator protocol, yield, and the itertools combinators you will reach for.

The iterator protocol 8 min
Generators with yield 9 min
itertools you will actually use 8 min
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Topic 7
Learning module

Functions, advanced

Default arguments, *args / **kwargs, lambdas, closures, and decorators — the patterns behind every framework.

*args, **kwargs, and defaults 9 min
Lambdas and higher-order functions 7 min
Closures and scope (LEGB) 8 min
Decorators explained 10 min
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Topic 8
Learning module

Python in practice

Strings, files, error handling, and small classes—patterns you use in every real script and service.

Strings, formatting, and parsing 16 min
try, except, and useful errors 15 min
Files and pathlib 16 min
Classes for structure (basics) 17 min
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Topic 9
Learning module

Object-oriented Python

Classes, inheritance, dunder methods, dataclasses, and properties — modeling real things with code.

Classes and instances 9 min
Inheritance and polymorphism 9 min
Dunder methods (operators) 9 min
Dataclasses 8 min
Properties and encapsulation 8 min
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Topic 11
Learning module

Standard library tour

datetime, json, re, collections, itertools, functools — the batteries you already have installed.

datetime essentials 8 min
json and csv 8 min
Regular expressions with re 9 min
The collections module 8 min
functools essentials 7 min
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Topic 12
Learning module

FastAPI and APIs

HTTP, JSON, and how to expose models and tools behind stable endpoints.

HTTP, JSON, and status codes 14 min
Routes and dependency injection 15 min
Serving models safely 15 min
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Topic 13
Learning module

Concurrency basics

Threads, processes, and asyncio — when to use which, and how to keep the GIL out of your way.

Threads vs processes vs async 9 min
asyncio fundamentals 10 min
Async iteration and task groups 8 min
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Topic 14
Learning module

Testing with pytest

Write fast, expressive tests with fixtures and parametrize so refactors stop being scary.

Writing your first tests 8 min
Fixtures and parametrize 8 min
Mocking external calls and coverage 8 min
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Topic 15
Learning module

Packaging and distribution

Project layout, pyproject.toml, virtual environments, and shipping a library other people can pip-install.

Project layout and virtual envs 8 min
pyproject.toml and publishing 9 min
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