Python is a high-level, general-purpose programming language designed around code readability and a deliberately small core syntax. The language has been steady at the top of TIOBE and PYPL indexes for years on the back of two distinct user bases: data and infrastructure engineers writing pipelines, and application developers building backends with Django or FastAPI.
What makes a Python codebase practical isn't the language itself but the ecosystem that comes with it. pip + uv for installs, pytest for tests, ruff + mypy for linting and types, poetry or pdm for project management. On the data side: pandas, polars, numpy, pytorch, scikit-learn.
What you'll work with in these 122 courses
- Core language: type hints, dataclasses, async/await, pattern matching
- Web backends: Django, FastAPI, Flask, async ORMs (SQLAlchemy 2.0, Tortoise)
- Data: pandas, polars, numpy, Apache Arrow, DuckDB
- Machine learning: PyTorch, scikit-learn, Hugging Face transformers, LangChain
- Infrastructure: Celery, Redis, FastAPI background tasks, Pydantic
- Testing and tooling: pytest, ruff, mypy, uv, poetry
Python runs the data layer at Instagram, the recommendation engine at Spotify, the build automation at Dropbox, scientific computing at CERN, and a growing share of LLM tooling at OpenAI, Anthropic, and Hugging Face.
