AI & Machine Learning Engineer Study Guide
Master Python, Linear Algebra, Neural Networks, PyTorch, and modern LLM / RAG architectures with zero paid courses.
Step-by-Step Curriculum
Follow each phase in order. Complete the hands-on project before moving to the next.
Python Foundations & Mathematical Intuition
Core Python, Matrix Multiplication, NumPy vectorization, and basic calculus intuition.
Build backpropagation and gradient descent from scratch without using PyTorch or TensorFlow.
Deep Learning & Neural Networks (PyTorch)
From backpropagation to Convolutional and Recurrent Networks using PyTorch.
Train a custom ResNet/Vision model on satellite or biomedical images and deploy with FastAPI.
Modern Generative AI, RAG & LLMs
Embeddings, Vector Databases, Retrieval-Augmented Generation (RAG), and fine-tuning with Hugging Face.
Build an AI agent that retrieves and answers questions against technical PDFs using embeddings and a free vector DB (e.g. Chroma/Qdrant).
Jobs Requiring These Skills
Active opportunities on Role Nest that look for the skills in this roadmap.