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
Python Playlists on Youtube
Top Twitter Creators
Python for Different Fields 🔗 Other Useful GitHub Repositories AI & Machine Learning with Python 🤖 Generative AI & Large Language Models
Resource Name
Link
Difficulty
PyTorch Official Tutorials
Click Here Intermediate
TensorFlow & Keras Guide
Click Here Intermediate
JAX Documentation
Click Here Advanced
Scikit-learn User Guide
Click Here Beginner
XGBoost Documentation
Click Here Intermediate
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
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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