AI Engineer Roadmap: Looking for Your Feedback

A developer named ArshiaLogic has created a roadmap for aspiring AI engineers, focusing on hands-on projects rather than tutorials. The roadmap covers Python, data science, machine learning, deep learning with PyTorch, transformers, Hugging Face, LLMs, RAG, LangChain, FastAPI, Docker, databases, and MLOps. The developer is seeking feedback on missing topics and learning order.

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 https://github.com/ArshiaLogic/ai-engineer-roadmap Thanks in advance I hope it can be useful for others as well. 😊