✦ 100% Free AI Curriculum

AI Literacy For
Every Profession

Whether you write code, design products, manage business ROI, or automate marketing pipelines — master custom AI workloads targeted directly at your career.

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5Curated Tracks
24Targeted Modules
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Contextual AI

No dry machine learning math. Learn how to consume APIs and deploy models directly.

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100% Free

Funded purely by non-intrusive sponsorships. No paywalls, no aggressive credit card prompt loops.

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Hands-on Labs

Run practical code in the sandbox. Build real agent pipelines, MCP servers, and vector databases.

Interactive Syllabus

Select Your Learning Path

Toggle the track buttons below to load customized modules designed for your industry.

Technical & Practical

Software Engineers Course

Learn the technical AI ecosystem inside out. Write Python, build pipelines, secure keys, and deploy autonomous systems.

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MODULE 01Beginner

What Is an LLM?

Understand how language models actually work — tokens, embeddings, attention, and why temperature matters — without any math.

5–6 hoursStart →
MODULE 02Beginner

Working with LLM APIs

Make real API calls, manage conversation history, handle streaming responses, and understand token costs.

5–6 hoursStart →
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MODULE 03Intermediate

Prompt Engineering

The 6 core strategies for writing prompts that reliably produce structured, useful output. Chain-of-thought, few-shot, JSON output.

6–8 hoursStart →
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MODULE 04Intermediate

RAG — Retrieval-Augmented Generation

Build a pipeline that loads, chunks, embeds, and retrieves your documents so the LLM can answer questions about private data.

6–8 hoursStart →
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MODULE 05Intermediate

AI Agents: Concepts & Architecture

What makes something an agent, the REACT loop, Andrew Ng's 4 agentic design patterns, memory types, and autonomy tradeoffs.

6–7 hoursStart →
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MODULE 06Intermediate

Building Agents with Frameworks

Hands-on with LangChain, CrewAI, and AutoGen. Build a single tool-use agent, a reflection loop, and a 2-agent pipeline.

8–10 hoursStart →
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MODULE 07Intermediate

MCP — Model Context Protocol

Anthropic's standard for connecting AI to tools. Build your own MCP server with tools, resources, and prompts.

7–9 hoursStart →
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MODULE 08Intermediate

Tools & Skills in AI Systems

Design tool schemas the model can reliably call. Learn how tools differ from skills, and build production-grade tools.

5–6 hoursStart →
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MODULE 09Intermediate

Evaluating & Debugging AI Systems

Build an eval harness with LLM-as-judge scoring. Detect hallucinations, catch prompt injection, set up observability tracing.

5–6 hoursStart →
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MODULE 10Advanced

Production & AI Safety

Cut costs 90% with prompt caching, secure your API keys, handle PII, set up monitoring, and know when to fine-tune.

4–5 hoursStart →
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MODULE 11Advanced

Capstone Project

Choose from 3 projects: an AI Code Review Agent, a Private Knowledge Assistant, or a Multi-Agent Research Pipeline.

10–15 hoursStart →
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MODULE 12Beginner

What Comes Next

Reasoning models, computer use agents, multimodal AI, research sources, and how to build a career in AI engineering.

2–3 hoursStart →
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