Alexandr Rich · Classroom

From curious
to capable.

Learn to build AI that works in the real world. A clear starting point, hands-on projects, and a path toward your next engineering role.

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Free lessons. No sign-up. Learn at your pace.

LESS WATCHING. MORE BUILDING.

01Learn the essentials

02Build something useful

03Prove it works

04Show teams your work

Your next chapter starts with one small project.

4 focused classes76 lessons & guides39 downloadable resources

The class library

One place. Your whole learning journey.

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CLASS 01 / 15 LESSONS

AI Engineer Path

A practical path from your starting point to a useful AI application and a focused job search.

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Build your foundations

CLASS 02 / 48 LESSONS

Learning Roadmap

Master LLMs, retrieval, agents, evaluation, deployment and practical machine learning.

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Build your portfolio

CLASS 03 / 7 LESSONS

Signal Project

Turn a real industry problem into a focused AI project that demonstrates what you can build.

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Find your next role

CLASS 04 / 6 LESSONS

Get Hired

Build your job-search pipeline, connect with teams, prepare applications and negotiate an offer.

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76 lessons

01AI Engineer Path · Choose your starting pointChoose the job you are preparing for 02AI Engineer Path · Choose your starting pointStart here: brand new to coding 03AI Engineer Path · Choose your starting pointStart here: experienced engineer 04AI Engineer Path · Choose your starting pointStart here: vibe coder 05AI Engineer Path · Build the core skillsThe smallest useful engineering foundation 06AI Engineer Path · Build the core skillsBuild one LLM feature you can measure 07AI Engineer Path · Build the core skillsMake answers traceable to evidence 08AI Engineer Path · Build the core skillsMake quality visible with an evaluation set 09AI Engineer Path · Build the core skillsShip an application another person can use 10AI Engineer Path · Build the core skillsAdd a bounded workflow, then consider an agent 11AI Engineer Path · Turn the work into a jobBuild one portfolio project worth discussing 12AI Engineer Path · Turn the work into a jobRun a focused job search while you build 13AI Engineer Path · Turn the work into a jobPrepare to explain, debug and design 14AI Engineer Path · Reference & toolsThe short watch list and course plan 15AI Engineer Path · Reference & toolsResearch notes, sources and toolkit 01Learning Roadmap · IntroductionProgram Structure (WATCH & READ FIRST)02Learning Roadmap · LLMs & RAGLLM Fundamentals 03Learning Roadmap · LLMs & RAGPrompt Engineering For Devs 04Learning Roadmap · LLMs & RAGWorking with LLM APIs 05Learning Roadmap · LLMs & RAGEmbeddings and Semantic Search 06Learning Roadmap · LLMs & RAGVector Databases 07Learning Roadmap · LLMs & RAGBasic Retrieval Augmented Generation (RAG)08Learning Roadmap · LLMs & RAGDocument Processing and Chunking 09Learning Roadmap · LLMs & RAGAdvanced Retrieval 10Learning Roadmap · LLMs & RAG🏁 CHECKPOINT PROJECT 11Learning Roadmap · Integration, Agents & OrchestrationFunction Calling and Tool Use 12Learning Roadmap · Integration, Agents & OrchestrationStructured Outputs and Validation 13Learning Roadmap · Integration, Agents & OrchestrationLLM applications with frameworks 14Learning Roadmap · Integration, Agents & OrchestrationAgent Fundamentals 15Learning Roadmap · Integration, Agents & OrchestrationAgentic Design Patterns 16Learning Roadmap · Integration, Agents & OrchestrationOrchestration with LangGraph 17Learning Roadmap · Integration, Agents & OrchestrationMulti Agent Intro 18Learning Roadmap · Integration, Agents & OrchestrationMulti-agent Systems 19Learning Roadmap · Integration, Agents & OrchestrationAgent Memory and State 20Learning Roadmap · Integration, Agents & OrchestrationAgentic RAG 21Learning Roadmap · Integration, Agents & OrchestrationModel Context Protocol (MCP)22Learning Roadmap · Integration, Agents & Orchestration🏁 CHECKPOINT PROJECT 23Learning Roadmap · Ops & EvaluationLLMOps Fundamentals 24Learning Roadmap · Ops & EvaluationServing Open Source Models 25Learning Roadmap · Ops & EvaluationDeploying LLM Applications 26Learning Roadmap · Ops & EvaluationObservability and Monitoring 27Learning Roadmap · Ops & EvaluationCI/CD for LLM Applications 28Learning Roadmap · Ops & EvaluationEvaluation Fundamentals 29Learning Roadmap · Ops & EvaluationLLM-as-a-Judge 30Learning Roadmap · Ops & EvaluationRAG Evaluation 31Learning Roadmap · Ops & EvaluationEvaluating AI Agents 32Learning Roadmap · Ops & EvaluationBenchmarking Models 33Learning Roadmap · Ops & Evaluation🏁 CHECKPOINT PROJECT 34Learning Roadmap · Safety & EthicsResponsible AI Practices 35Learning Roadmap · Safety & EthicsData Ethics and Bias 36Learning Roadmap · Safety & EthicsLLM Security and Risk 37Learning Roadmap · Safety & EthicsGuardrails 38Learning Roadmap · Safety & EthicsAI Governance and Frameworks 39Learning Roadmap · Safety & Ethics🔑 Resource 40Learning Roadmap · Safety & Ethics🏁 CHECKPOINT PROJECT 41Learning Roadmap · ML FoundationsML Fundamentals and Metrics 42Learning Roadmap · ML Foundationsscikit-learn: Pipelines and Model Training 43Learning Roadmap · ML FoundationsData Engineering and Quality 44Learning Roadmap · ML FoundationsExperiment Tracking with MLflow 45Learning Roadmap · ML FoundationsData Versioning with DVC 46Learning Roadmap · ML FoundationsDeployment and CI/CD 47Learning Roadmap · ML FoundationsMonitoring ML in Production 48Learning Roadmap · ML Foundations🏁 CHECKPOINT PROJECT 01Signal Project · LessonsHow to Build a Project to Get Hired!02Signal Project · Resume Project Steps1. Target 03Signal Project · Resume Project Steps2. Market Research 04Signal Project · Resume Project Steps3. Problem Selection & Expert Depth 05Signal Project · Resume Project Steps4. AI System Architecture 06Signal Project · Resume Project Steps5. Team & Build 07Signal Project · Resume Project Steps6. Launch & Signal 01Get Hired · LessonsHow to Get Hired Overview 02Get Hired · LessonsApply, Track, & Convert 03Get Hired · LessonsWarm Paths 04Get Hired · LessonsCold Paths Direct to Decision Makers 05Get Hired · LessonsBuild the Pipeline 06Get Hired · LessonsNegotiate

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