A comprehensive, hands-on Python curriculum spanning 132 programs across 18 phases — from syntax basics to production-grade AI systems. Designed for learners, educators, and practitioners who want a structured end-to-end journey through modern Python development.
- Overview
- Curriculum Map
- Getting Started
- Prerequisites
- Usage
- Phase Details
- Tech Stack
- Project Structure
- Contributing
- License
| Metric | Count |
|---|---|
| Programs | 132 |
| Phases | 18 |
| Topics | 130+ |
| Python Version | 3.13+ |
| External Packages | 30+ |
This repository is a progressive, project-driven curriculum that takes you from zero Python knowledge to building distributed AI inference platforms. Each file is self-contained, runnable, and includes practical examples with real-world relevance.
Phase 1: Python Basics → 12 programs (Hello World → Virtual Environments)
Phase 2: Data Structures → 8 programs (Lists → collections Module)
Phase 3: Strings → 4 programs (Manipulation → Parsing)
Phase 4: OOP → 12 programs (Classes → Descriptors)
Phase 5: Files → 6 programs (Reading → YAML Parsing)
Phase 6: Exceptions → 3 programs (Handling → Context Managers)
Phase 7: Advanced Python → 9 programs (Decorators → Monkey Patching)
Phase 8: Concurrency → 6 programs (Threading → Producer-Consumer)
Phase 9: Databases → 5 programs (SQLite → Redis)
Phase 10: Web Development → 6 programs (Flask → WebSockets)
Phase 11: Data Structures & Algo → 15 programs (Linked List → Greedy)
Phase 12: Testing → 4 programs (unittest → Integration Testing)
Phase 13: DevOps → 4 programs (Docker → CI/CD)
Phase 14: Machine Learning → 6 programs (NumPy → Model Evaluation)
Phase 15: Deep Learning → 9 programs (PyTorch → Fine-tuning LLMs)
Phase 16: AI Systems → 11 programs (Tokenizers → Inference Engine)
Phase 17: System Design Projects → 12 programs (URL Shortener → Distributed AI)
# Clone the repository
git clone https://github.com/<your-username>/Python-Programming.git
cd Python-Programming
# (Optional) Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Run any program
python "Phase 1: Python Basics/01_hello_world.py"- Python 3.13+ (Download)
- pip (included with Python 3.13+)
- Optional: Docker, PostgreSQL, Redis
Some later phases require external packages. Each file has inline pip install instructions. You can install all optional dependencies at once:
pip install flask fastapi uvicorn sqlalchemy alembic psycopg2-binary redis \
pyyaml pytest pytest-mock torch torchvision numpy pandas \
scikit-learn matplotlib transformers datasets sentence-transformers \
chromadb uvicorn dockerEvery file is a standalone script with a main() function:
cd "Phase 1: Python Basics"
python 01_hello_world.pyFiles in Phases 9+ may require running services (PostgreSQL, Redis, etc.) and gracefully degrade with setup instructions when those services are unavailable.
12 programs — Start here if you're new to Python. Covers syntax, data types, control flow, functions (01_hello_world.py → 12_virtual_environments.py).
8 programs — Built-in collections: lists, tuples, sets, dicts, comprehensions, iterators, generators, and the collections module.
4 programs — String manipulation, regular expressions, text processing, and parsing techniques.
12 programs — Deep dive into object-oriented programming: classes, inheritance, polymorphism, encapsulation, abstraction, magic methods, dataclasses, properties, and descriptors.
6 programs — File I/O across formats: plain text, CSV, JSON, XML, and YAML.
3 programs — Exception handling best practices, custom exceptions, and context managers.
9 programs — Functional and metaprogramming: decorators, closures, lambdas, functools, itertools, contextlib, metaclasses, and monkey patching.
6 programs — Parallel and async programming: threading, multiprocessing, asyncio, coroutines, queues, and the producer-consumer pattern.
5 programs — SQLite, PostgreSQL, SQLAlchemy ORM, Alembic migrations, and Redis caching.
6 programs — Web APIs with Flask and FastAPI, JWT authentication, REST design, and WebSocket communication.
15 programs (2 subdirectories) — Classic DS (linked lists, stacks, queues, heaps, tries, BSTs, AVL trees, graphs) and algorithms (BFS, DFS, Dijkstra, Bellman-Ford, DP, backtracking, greedy).
4 programs — unittest, pytest, mocking, and integration testing patterns.
4 programs — Dockerfiles, structured logging, monitoring, and CI/CD pipeline examples.
6 programs — NumPy, pandas, Matplotlib, scikit-learn, feature engineering, and model evaluation.
9 programs — PyTorch fundamentals (tensors, autograd, neural networks), CNNs, RNNs, LSTMs, Transformers, and LLM fine-tuning.
11 programs — Production AI: tokenizers, attention mechanisms, multi-head attention, KV-cache, transformer blocks, state-space models, quantization, vector databases, RAG pipelines, model serving, and inference engines.
12 programs — Capstone projects: URL shortener, chat app, search engine, recommendation system, distributed cache, task queue, workflow engine, agent frameworks, multi-agent systems, LLM serving, vector search, and distributed AI inference.
| Category | Technologies |
|---|---|
| Languages | Python 3.13+ |
| Web | Flask, FastAPI, Uvicorn, WebSockets |
| Databases | SQLite, PostgreSQL, Redis, ChromaDB |
| ORMs | SQLAlchemy, Alembic |
| ML/DL | NumPy, pandas, scikit-learn, PyTorch, Transformers |
| Infrastructure | Docker, YAML, Git |
| Testing | unittest, pytest, pytest-mock |
Python-Programming/
├── Phase 1: Python Basics/ (12 programs)
├── Phase 2: Data Structures/ ( 8 programs)
├── Phase 3: Strings/ ( 4 programs)
├── Phase 4: OOP/ (12 programs)
├── Phase 5: Files/ ( 6 programs)
├── Phase 6: Exceptions/ ( 3 programs)
├── Phase 7: Advanced Python/ ( 9 programs)
├── Phase 8: Concurrency/ ( 6 programs)
├── Phase 9: Databases/ ( 5 programs)
├── Phase 10: Web Development/ ( 6 programs)
├── Phase 11: Data Structures & Algorithms/
│ ├── 01_Data_Structures/ ( 8 programs)
│ └── 02_Algorithms/ ( 7 programs)
├── Phase 12: Testing/ ( 4 programs)
├── Phase 13: DevOps/ ( 4 programs)
├── Phase 14: Machine Learning/ ( 6 programs)
├── Phase 15: Deep Learning/ ( 9 programs)
├── Phase 16: AI Systems/ (11 programs)
├── Phase 17: System Design Projects/ (12 programs)
├── README.md
├── LICENSE
└── CODE_OF_CONDUCT.md
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
See CONTRIBUTING.md for detailed guidelines.
Distributed under the MIT License. See LICENSE for more information.
- Inspired by the comprehensive Python learning paths from real-world software engineering and AI engineering curricula.
- Built with passion for the Python community.
⭐ Star this repo if you find it useful! ⭐