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Career Path

AI Engineer Career Path

A complete, free path to an AI engineer role — Python, then the full Generative AI & LLM Engineering stack: prompting, tools, RAG, agents, and deployment.

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At a glance

Level
Intermediate to Advanced
Lessons
80 lessons
Duration
4–6 months
Projects
12+ projects

Become the engineer who ships AI features. Start with Python, then build the entire modern LLM stack hands-on — prompting, tool use, the Model Context Protocol, embeddings, vector databases, retrieval-augmented generation, autonomous agents, LangChain and LangGraph, and production deployment — every concept verified with real, runnable code on Claude.

What you'll learn

  • Python programming, the language of AI engineering
  • How LLMs work and how to call them from code
  • Prompt engineering and structured outputs
  • Tool use, function calling, and the Model Context Protocol
  • Embeddings, vector databases, and semantic search
  • Retrieval-augmented generation (RAG) over your own data
  • Building autonomous agents, with and without frameworks
  • Shipping reliable, affordable, secure AI services

Your learning path

Work through the phases in order. Each card is a full course you can start right now.

Phase 1 — Python Foundations

No programming background required. Skip if you already know Python.

Beginner Python Basics Variables, control flow, functions, and core data structures. Variables & data types · Loops & conditionals · Functions & modules · Lists & dictionaries 14 lessons 4–6 weeks Start module Intermediate Python Advanced Object-oriented programming, decorators, generators, and clean Python patterns you'll use in every AI project. OOP · Decorators & closures · Generators · Context managers 14 lessons 4–6 weeks Start module

Phase 2 — LLM Fundamentals

The core of working with language models in code.

Beginner to Intermediate Working with LLMs in Python How LLMs work, your first API calls, messages, tokens, and a command-line assistant project. How LLMs work · The Messages API · Tokens & usage · System prompts 7 lessons 2–3 weeks Start module Intermediate Prompt Engineering Write reliable prompts: structure, few-shot examples, structured outputs, and evaluation. Prompt anatomy · Few-shot prompting · Structured outputs · Prompt evaluation 8 lessons 2–3 weeks Start module

Phase 3 — Tools & Retrieval

Connect models to real tools and your own data.

Intermediate Tool Use & Function Calling Give models tools: define schemas, run the tool-use loop, and build a multi-tool assistant. Tool definitions · The tool-use loop · Parallel tools · Multi-tool agents 5 lessons 1–2 weeks Start module Intermediate Model Context Protocol (MCP) The open standard for AI tools: connect to MCP servers, build your own, and bridge them to Claude. What MCP is · MCP clients · Building servers · Bridging to Claude 4 lessons 1 week Start module Intermediate Embeddings & Semantic Search Turn text into vectors that capture meaning, and build a semantic search engine. What embeddings are · Generating embeddings · Cosine similarity · Semantic search 4 lessons 1 week Start module Intermediate Vector Databases Store and search embeddings at scale with Chroma — metadata filtering, persistence, and a knowledge base. Why vector databases · Chroma basics · Metadata filtering · Persistence 4 lessons 1 week Start module Intermediate Retrieval-Augmented Generation Ground a model in your own documents: build a RAG pipeline, chunk well, and cite sources. What RAG is · RAG pipelines · Chunking · Grounding & citations 5 lessons 1–2 weeks Start module

Phase 4 — Agents & Shipping

Build autonomous systems and put them in production.

Advanced Building AI Agents Agents that decide their own steps: the agent loop, memory, tools, planning, and a research assistant. The agent loop · Memory & tools · Planning · Multi-step tasks 5 lessons 1–2 weeks Start module Advanced LangChain & LangGraph Build faster with frameworks: LCEL chains, RAG with LangChain, and stateful agents with LangGraph. LCEL chains · RAG with LangChain · LangGraph agents · Memory & checkpoints 5 lessons 1–2 weeks Start module Advanced Shipping AI Applications Take prototypes to production: streaming, error handling, cost control, security, and serving with FastAPI. Streaming & retries · Cost & tokens · Securing keys · Serving with FastAPI 5 lessons 1–2 weeks Start module

Where this path can take you

Skills from this path map directly to roles like:

  • AI Engineer
  • LLM Engineer
  • Applied AI Developer
  • Machine Learning Engineer
  • AI Application Developer
100% Free

No hidden costs, no premium tiers

Project-Based

Build real projects for your portfolio

Self-Paced

Learn at your own speed, no deadlines

Ready to become an AI Engineer?

Begin with the first course and work through the complete path at your own pace.

Start the first lesson