All Pathways
🧠

ML / AI Engineer

6 courses · ~16 weeks

From Python fundamentals to neural networks, RAG pipelines, and prompt engineering. This pathway prepares you to build and deploy machine learning systems and ace ML-focused interviews.

Prepares you for

ML EngineerAI EngineerData ScientistApplied ScientistNLP Engineer

Interview types covered

TechnicalSystem DesignRecruiter Screen

Course Sequence

1
🐍

Python Fundamentals: From Zero to Programmer

PRO

Learn Python from scratch. 10 modules covering variables, control flow, functions, data structures, OOP, and real projects — all with hands-on exercises.

2
🤖

AI & Machine Learning Fundamentals

PRO

Master the foundations of AI and machine learning from scratch. Build linear regression, logistic regression, neural networks, CNNs, and NLP pipelines using only NumPy — no frameworks, just understanding.

3
🧠

Neural Networks: Zero to Hero

PRO

Build neural networks from scratch, progressing from micrograd to GPT. Based on Andrej Karpathy's legendary course — covers backpropagation, language modeling, transformers, and tokenization.

4
📚

RAG Engineering: Build Production Retrieval Systems

PRO

Master Retrieval-Augmented Generation from fundamentals to production. Learn vector databases, chunking strategies, query enhancement, hybrid search, reranking, Graph RAG, RAPTOR, Self-RAG, CRAG, and production deployment. Based on the RAG Techniques repository (25.9k stars).

5
✨

Prompt Engineering Masterclass

PRO

Master the art and science of prompting LLMs. Covers zero-shot, few-shot, chain-of-thought, RAG, ReAct, model-specific strategies, safety, and production deployment.

6
🤖

Machine Learning Interview Prep

PRO

Prepare for ML interviews covering fundamentals, algorithms, deep learning, and real-world ML system design problems like search ranking, recommendations, and ad prediction.

Estimated completion: ~16 weeks at 10 hrs/week