Zero to AI Engineer

From Your First Neuron to Production AI Systems

The complete journey — AI foundations, neural networks, generative AI, LangChain, MCP, and edge AI, all the way to production engineering. Explained simply and visually, from zero experience to building real AI systems. Adapted from Microsoft's open curricula.

Beginner54 modules6-9 monthsAnyone going from zero to a career in AI engineering

Curriculum Modules

54 modules covering everything from fundamentals to advanced topics.

Capstone Project

Put everything together in a comprehensive final project that demonstrates your mastery. Includes real-world problem solving, documentation, and portfolio-ready deliverables.

View Capstone Details

Zero to AI Engineer

Curriculum Modules

Module 1: What Is Artificial Intelligence?

Module 2: Symbolic AI & Knowledge Representation

Module 3: Machine Learning Basics

Module 4: How Neural Networks Work

Module 5: Training Neural Networks

Module 6: Computer Vision & CNNs

Module 7: Natural Language Processing

Module 8: Transformers & Modern Language Models

Module 9: Reinforcement Learning & Other AI

Module 10: AI Ethics & Responsible AI

Module 11: What Is Generative AI?

Module 12: How Large Language Models Work

Module 13: Prompting & Using LLMs

Module 14: LLM Safety & Responsible Use

Module 15: LangChain Fundamentals

Module 16: Chat Models in LangChain

Module 17: Prompts, Messages & Output Parsing

Module 18: Function Calling & Tools

Module 19: Building LangChain Agents

Module 20: Documents, Embeddings & Semantic Search

Module 21: Vector Stores & RAG

Module 22: Agentic RAG Systems

Module 23: MCP Fundamentals

Module 24: MCP Core Concepts — Hosts, Clients & Servers

Module 25: MCP Building Blocks — Tools, Resources & Prompts

Module 26: Building Your First MCP Server

Module 27: Building an MCP Client

Module 28: MCP Security

Module 29: MCP Best Practices & Advanced Topics

Module 30: MCP in the Real World — Case Studies

Module 31: Edge AI Fundamentals

Module 32: Small Language Models & the Phi Family

Module 33: Model Optimization & Quantization

Module 34: Deploying Models on Devices

Module 35: SLMOps — Operating Models at the Edge

Module 36: Edge AI Agents

Module 37: Real-World Edge AI & Device Constraints

Module 38: Software Engineering for AI

Module 39: ML System Design

Module 40: ML Pipelines

Module 41: Model Training at Scale

Module 42: Model Serving

Module 43: Feature Stores

Module 44: Experiment Tracking

Module 45: CI/CD for ML

Module 46: Monitoring & Observability

Module 47: Cloud AI Services

Module 48: Kubernetes for AI

Module 49: Cost Optimization

Module 50: Real-World AI Engineering Workflows

Module 51: End-to-End Capstone Project

Module 52: Knowledge Check

Module 53: Glossary of AI Engineering Terms

Module 54: Your Zero-to-AI-Engineer Roadmap & Next Steps

Capstone Project