3 training tracks, 90+ lessons, 20 podcast episodes

Master AI. Build with confidence.

From LLMs and RAG to Claude Code, MCP servers, and production deployment. A structured curriculum for engineers, architects, and AI leaders.

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3 free chaptersLifetime accessFree updates

How AI systems evolved

Three generations of AI architecture

Each generation builds on the last. Understanding all three is what separates engineers who use AI from engineers who build with it.

Generation 1

LLMs

Predict the next token

Transformer architecture processes tokens in parallel, not sequentially like RNNs
Trained on trillions of tokens. GPT-4, Claude Opus, Gemini, Llama, DeepSeek all share this foundation
Stateless: no memory between conversations, no access to tools or live data

What you can build

Chatbots, code completion, text summarization, translation, content generation

Generation 2

RAG

Retrieve, then generate

Embeds your documents into vectors, retrieves relevant chunks at query time, and feeds them as context
Hybrid search (BM25 + semantic) with reranking solves the "wrong document" problem that trips up naive RAG
Still reactive: waits for prompts. No planning, no tool use, no multi-step reasoning

What you can build

Knowledge bases, support bots with citations, document Q&A, enterprise search

Generation 3

Agentic AI

Plan, reason, act, learn

Agents call tools, read files, run code, and make decisions across multi-step workflows autonomously
MCP connects agents to any system. A2A lets agents collaborate. 97M monthly SDK downloads and growing
Self-improving: Claude's Dreaming feature reviews past sessions to find patterns. Outcomes defines success rubrics so agents can score and retry their own work

What you can build

Autonomous coding, research agents, CI/CD pipelines, multi-agent orchestration

Predicting words→Retrieving facts→Achieving goals

This course covers all three. Most training stops at the first.

Chapters

Programs

Lessons

Episodes

Tracks

AI FoundationsFree to start

Understand how AI actually works

17 structured chapters from GPT architecture to enterprise AI strategy. Covers LLMs, RAG, agentic AI, MCP, Docker, CI/CD, monitoring, enterprise AI organization, ML model deployment, MCP workflows, and LangChain vs LangGraph. Start with 3 free chapters.

17 chapters 3 free Capstone project

Explore Course

17 Chapters across 4 tracks

FREE

Ch 1-3: Core Foundations

LLMs, GPT, transformers, RAG, embeddings, vector DBs, agentic AI, reasoning, safety, benchmarks

STARTER

Ch 4-5: Integration & Building

MCP protocol, cloud platforms (AWS, GCP, Azure), SDKs, building AI systems, production architecture

PRO

Ch 6-10: Build & Ship

Capstone project, Docker deployment, web UI, async scaling, production monitoring with LangFuse

PRO

Ch 11-17: Enterprise & Advanced

Enterprise AI org (20+ case studies), Claude enablement, MCP deep dive, ML model deployment (vLLM, Triton, cloud), MCP workflows with guardrails, LangChain vs LangGraph

Claude TrainingWith Certification

Master the full Claude ecosystem

10 training programs covering prompting, Claude Code, API development, MCP servers, Skills authoring, Vertex AI, enterprise administration, and more. Pass the quiz, earn the certificate.

10 programs 69 lessons Certificates

Explore Training

10 Programs across 69 lessons

Core Skills

Prompting essentials, models & tokens, system prompts, tool use, coding with Claude, apps & artifacts

Claude Code Mastery

CLAUDE.md, workflows, subagents, hooks, parallelization, Agent View, GitHub integration, custom commands

API, MCP & Skills

Messages API, streaming, tool use, RAG, MCP server dev, client implementation, transports, skill authoring

Vertex AI & Enterprise

Claude on GCP, SSO/SCIM, audit logs, managed settings, policy flow, gateway architecture, seat management

AI Evals CourseAvailable Now

Evaluate AI systems rigorously

Build test datasets, run prompt evaluations, implement model-based and code-based grading, and create continuous eval pipelines. 8 weeks plus a capstone project.

8 modules Capstone project Certificate

Start Course

8 Modules + Capstone

Foundations & Lifecycle

Business alignment, eval lifecycle, instrumentation

Systematic Error Analysis

Sampling, open coding, failure taxonomies

Evaluators That Stick

Code grading, LLM-as-judge, rubric design

Alignment & Collaboration

Inter-annotator agreement, governance loops

Architecture-Specific

RAG (RAGAS), agents, multi-turn, summarization

Production Monitoring

CI gates, drift detection, A/B testing

Human Review Workflows

Annotation, red teaming, safety evaluation

Cost Optimization

Model cascading, batch APIs, ROI analysis

Capstone Project

End-to-end eval pipeline + certificate

What you get

Everything in one platform

Not just text. Interactive lessons, podcast episodes, certification quizzes, code examples, architecture diagrams, and production checklists.

Deep-dive chapters

From GPT architecture to Kubernetes auto-scaling. Each chapter builds on the previous one.

Hands-on lessons

Code examples, exercises, and real-world scenarios across Claude Code, API, MCP, Skills, and more.

Certification programs

Pass the master quiz (80%+) and earn a downloadable certificate. Add it to LinkedIn or share with your team.

Podcast episodes

Listen while you commute. Two engineers break down every topic from prompting to production MCP servers.

NEW SEASON20 Episodes~6 Hours

AI Training Unpacked

The podcast for engineers building with Claude.

Two engineers break down everything from how Claude processes text to building production MCP servers, cost optimization, security compliance, and curriculum design. No fluff, just the concepts and code you actually need. Listen while you commute, exercise, or code.

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What you can expect

S1 E1-5