Hi everyone! 👋
Over the past few weeks, I've been putting together a roadmap for anyone who wants to become an AI Engineer through hands-on projects rather than only watching tutorials.
The roadmap covers topics such as:
🐍 Python
📊 Data Science
🤖 Machine Learning
🧠 Deep Learning (PyTorch) 🔄 Transformers
🤗 Hugging Face
💬 Large Language Models (LLMs)
📚 RAG (Retrieval-Augmented Generation)
🔗 LangChain & LangGraph
⚡ FastAPI
🐳 Docker
🗄️ Databases
🚀 MLOps
My goal is to keep improving it and eventually turn it into a practical, project-based guide for aspiring AI Engineers.
I'd really appreciate your feedback:
Is there anything important I'm missing?
Would you change the learning order?
Any topics you think should be added or removed?
You can find the roadmap here:
👉 https://github.com/ArshiaLogic/ai-engineer-roadmap Thanks in advance! I hope it can be useful for others as well. 😊