Master the Python fundamentals specifically required for modern AI engineering, bypassing web-dev fluff.


# Modern Python Setup

Gone are the days of managing `requirements.txt` manually or fighting with `conda`. In 2024, we use **uv**.

## Why UV?

UV is a lightning-fast Python package installer and resolver, written in Rust. It's designed to be a drop-in replacement for `pip` and `pip-tools`.

### Installation

```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```

### Creating a Virtual Environment

```bash
uv venv
source .venv/bin/activate
```
        

Modern Python Setup & UV


# Advanced Typing in Python

Python is dynamically typed, but for production AI systems, strict typing is essential to catch errors early.

## Type Hints

Type hints help IDEs and static analysis tools check your code.

```python
def process_items(items: list[str]) -> int:
    return len(items)
```
        

Advanced Typing & Generics

Learn how to manage concurrent requests to OpenAI...

Async Patterns for API Calls

Structure your LLM outputs using Pydantic models...

Data Validation with Pydantic

Build custom decorators to trace agent execution...

Decorators for Observability

This course focuses purely on the Python features used in AI: typing, async/await, decorators, Pydantic, and efficient data handling. No Django, no basic loops—just high-performance engineering patterns.

Python AI Project for Beginners

Get set up with VS Code and Python, learn the VS Code UI, essential extensions, hotkeys, and how to run Interactive Python.

Visual Studio Code Setup

Create, activate, and manage Python virtual environments for AI projects to avoid dependency conflicts across multiple projects.

Python Virtual Environments

Learn how to use uv to manage Python versions, initialize projects, install dependencies, and run scripts with a clean, reproducible workflow.

Python AI Project for Beginners

What You'll Learn

Course Curriculum

Module 1: Core Concepts

Visual Studio Code Setup

Python Virtual Environments

UV Package Manager