Learn Python
Introduction 💫
Python is a high-level, interpreted scripting language, highly used for automation and backend purposes.
People from different disciplines use Python for a variety of different tasks, such as data analysis and visualization, artificial intelligence and Machine Learning,
automation, etc.
It is a language that many people fall in love with because of its simplicity. The syntax is simple and the debugging is also much easier in Python compared to languages like C++ or C# even though Python was made using C++ in 1991 by Guido van Rossum.
Index
General 🔗
Index 📑
Basic Resources 🔗
Python Playlists on Youtube
Top Youtube Creators
Top Blogs
Cheatsheets 🗒️
Top Twitter Creators
Top Podcasts
Python for Different Fields 🔗
Other Useful GitHub Repositories
AI & Machine Learning with Python 🤖
Generative AI & Large Language Models
Modern ML Frameworks
Vector Databases & RAG
AI/ML YouTube Playlists
| Resource Name | Link | Difficulty |
|---|
| Andrej Karpathy - Neural Networks: Zero to Hero | Click Here | Intermediate |
| 3Blue1Brown - Neural Networks | Click Here | Beginner |
| Fast.ai Practical Deep Learning | Click Here | Intermediate |
| Sentdex - ML with Python | Click Here | Beginner |
| DeepLearning.AI Short Courses | Click Here | Beginner |
Books & Documentation
| Resource Name | Link | Difficulty |
|---|
| Hands-On Machine Learning (3rd Ed.) | Click Here | Intermediate |
| Deep Learning with Python - Chollet | Click Here | Intermediate |
| NLP with Transformers | Click Here | Intermediate |
| OpenAI Cookbook | Click Here | Beginner |
| Hugging Face Course (Free) | Click Here | Beginner |
AI/ML Blogs & Communities
AI Coding Agents for Python Development 🧑💻
| Resource Name | Link | Notes |
|---|
| Claude Code | Click Here | Terminal agent, strong at Python codebase understanding & refactors |
| Cursor | Click Here | AI-first VS Code fork, great Python autocomplete + Composer |
| GitHub Copilot | Click Here | Python-aware autocomplete & agent mode in most IDEs |
| OpenAI Codex CLI | Click Here | Terminal coding agent, solid for Python scripting tasks |
| Cline | Click Here | Open-source VS Code agent, writes & runs Python directly |
| Aider | Click Here | Git-aware pair programming in the terminal, Python-first UX |
Building AI Agents in Python 🤖
| Resource Name | Link | Notes |
|---|
| LangGraph | Click Here | Python framework for stateful, controllable multi-agent apps |
| CrewAI | Click Here | Pure-Python role-based multi-agent framework |
| AG2 (formerly AutoGen) | Click Here | Python framework for conversational multi-agent systems |
| Semantic Kernel (Python) | Click Here | Microsoft's agent SDK, first-class Python support |
| OpenAI Agents SDK | Click Here | Lightweight Python agent + handoff primitives |
| Smolagents (Hugging Face) | Click Here | ~1000-line minimal Python agent loop, easy to learn from |
| LlamaIndex Workflows | Click Here | Python event-driven agent orchestration |
| Pydantic AI | Click Here | Type-safe Python agent framework from the Pydantic team |
Model Context Protocol (MCP) with Python 🔌
| Resource Name | Link | Notes |
|---|
| MCP Official Docs & Spec | Click Here | Protocol spec + Python SDK guide |
| Python MCP SDK | Click Here | Official Python SDK for building MCP servers/clients |
| MCP Reference Servers | Click Here | Official reference servers, many written in Python |
| Awesome MCP Servers | Click Here | Curated directory of MCP servers (filter by Python) |
Evaluating & Testing LLM Apps in Python 📊
| Resource Name | Link | Notes |
|---|
| LangSmith | Click Here | Python SDK for tracing, evals, and monitoring LLM apps |
| Comet Opik | Click Here | Open-source Python library for LLM observability & evals |
| Promptfoo | Click Here | Prompt testing & red-teaming, works with Python pipelines |
| Weights & Biases Weave | Click Here | Python-native tracking & evaluation for LLM apps |
Running Local & Open-Source LLMs with Python 🖥️
| Resource Name | Link | Notes |
|---|
| Ollama Python Library | Click Here | Official Python client for running local models via Ollama |
| llama-cpp-python | Click Here | Python bindings for llama.cpp, run GGUF models directly |
| vLLM | Click Here | Python library for high-throughput LLM inference & serving |
| Hugging Face Transformers | Click Here | The standard Python library for loading & running open models |
| Hugging Face Hub | Click Here | Browse open models/datasets to load via the Python huggingface_hub library |
Build an LLM From Scratch in Python 🔬
For people who want to go past "calling an API" and actually understand what's happening inside the model.
| Resource Name | Link | Notes |
|---|
| Build a Large Language Model (From Scratch) : Raschka | Click Here | Companion Python/PyTorch repo; builds tokenizer → attention → GPT → training loop by hand |
| nanoGPT : Karpathy | Click Here | ~300-line, dependency-light GPT training/inference in pure PyTorch |
| Neural Networks: Zero to Hero :Karpathy | Click Here | Video series that codes backprop, a tokenizer, and a GPT from raw Python |
| Let's Build the GPT Tokenizer :Karpathy | Click Here | Builds a BPE tokenizer in Python line by line |
| Annotated Transformer : Harvard NLP | Click Here | "Attention Is All You Need" paper reproduced as runnable PyTorch code |
| CS231n / CS224n course notes | Click Here | Stanford's deep learning & NLP course notes, Python-based assignments |
Fine-Tuning LLMs in Python (PEFT, LoRA, QLoRA) 🎛️
| Resource Name | Link | Notes |
|---|
| Hugging Face PEFT | Link | The standard Python library for LoRA/QLoRA and other efficient fine-tuning methods |
| Hugging Face PEFT Docs | Link | Task-by-task guides (text, vision, speech) |
| TRL (Transformer Reinforcement Learning) | Link | Python library for SFT, DPO, and RLHF-style fine-tuning |
| bitsandbytes | Link | 4-bit/8-bit quantization used for QLoRA on consumer GPUs |
| Unsloth | Link | Faster, lower-memory Python library for fine-tuning open LLMs |
| Axolotl | Link | YAML-configured Python fine-tuning framework built on PEFT/TRL |
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