GenAI Complete Program — Product Led Hub
Gen AI Stack Certificate

From First API Call
to Autonomous Systems

Two certificates. Sixteen modules. One complete engineering path — from TypeScript fundamentals and LLM integration through advanced prompting patterns, hybrid RAG+KAG, multimodal AI, and enterprise-grade autonomous agents.

Learn More Get Certified
8
Foundations Modules
8
Architecture Modules
30+
Hours of Content
2
Capstone Projects
TS
TypeScript Native
Two Certificates

One Continuous
Learning Path Get Certified

Track 1 — Level 1
GenAI Foundations Certificate
Build strong conceptual and practical foundations. TypeScript essentials, LLM integration, RAG pipelines, basic agent frameworks, and real-world web applications — everything you need to ship production AI features.
TypeScript LLM SDKs RAG LangChain Mastra React Apps Ethics
8 modules  ·  15+ hours  ·  No prerequisites
Track 2 — Level 2
GenAI Architecture Certificate
Elevate from integration to system design. Advanced prompting patterns, hybrid RAG+KAG with knowledge graphs, multimodal AI, enterprise observability, prompt engineering UIs, and autonomous multi-agent systems.
CoT / ReAct GraphRAG KAG Multimodal Agents LangGraph Enterprise
8 modules  ·  15+ hours  ·  Foundations required
Learning Pathway
→ Track 1: GenAI Foundations Certificate
M01
TS Fundamentals
M02
GenAI Foundations
M03
Working with LLMs
M04
RAG Systems
M05
Agent Frameworks
M06
Web Applications
M07
Ethics & Security
M08
Capstone I
→ Track 2: GenAI Architecture Certificate
M01
Advanced Prompting
M02
RAG + KAG
M03
Multimodal AI
M04
Advanced Patterns
M05
Enterprise Systems
M06
Prompt UI
M07
AI Agents
M08
Capstone II
Track 1

Foundations Certificate
— All 8 Modules Get Certified

Build the complete engineering toolkit: TypeScript, LLM APIs, RAG, agents, and real-world web apps. No prerequisites required.

GenAI Foundations Certificate
8 modules  ·  15+ hours  ·  Capstone Project
F-01 // Fundamentals
Fundamentals for AI Engineers
TypeScript types, interfaces, generics, async/await, streaming patterns, Zod validation, error handling, and building AI backends with Node.js and Express.
TypeScriptAsync/AwaitZodExpress
F-02 // Foundations
Foundations of Generative AI
How LLMs work: tokenization, context windows, model selection, cost estimation, prompt engineering fundamentals, embeddings, and a RAG conceptual introduction. Hands-on first API calls.
LLMsEmbeddingsPrompt Eng.RAG Intro
F-03 // Integration
Working with LLMs using TypeScript
OpenAI, Anthropic, Gemini, and Vercel AI SDKs. Streaming responses, function calling, tool use, error handling, content moderation, and advanced prompting techniques.
OpenAI SDKClaudeStreamingTool Use
F-04 // Retrieval
RAG with TypeScript
Document chunking, vector databases (pgvector, Pinecone, Weaviate, Qdrant), LangChain MemoryVectorStore, OpenAI embeddings, and Mastra framework integration end-to-end.
RAGLangChainPineconeMastra
F-05 // Agents
AI Frameworks & Agent Development
Agentic AI with Mastra, VoltAgent, and LLM-EXE. Tool use, memory, multi-provider APIs, function calling, Zod-typed workflows, and building specialised agents.
AgentsMastraVoltAgentMemory
F-06 // Applications
Building Real-World GenAI Web Apps
End-to-end GenAI apps with React, Node.js, Express, and LangChain. Chatbots with chat history, NestJS backends, Redux state, and deployment strategies.
ReactNestJSLangChainDeploy
F-07 // Ethics & Security
Ethics, Evaluation & Security
Bias and hallucination detection, model evaluation metrics, EU AI Act, compliance, multimodal search, and security pipelines for production AI systems.
EthicsEvaluationEU AI ActSecurity
F-08 // Capstone
Final Project — Capstone I
Build and present a complete GenAI application: a RAG Q&A system, autonomous agent, multimodal app, or domain-specific chatbot — simulating a real-world deploy scenario.
CapstoneRAGMultimodalDeploy
Track 2

Architecture Certificate
— All 8 Modules Get Certified

Advanced system design: sophisticated prompting, hybrid retrieval with knowledge graphs, multimodal pipelines, enterprise observability, and autonomous agents.

GenAI Architecture Certificate
8 modules  ·  15+ hours  ·  Foundations required
A-01 // Prompting
Advanced Prompt Engineering Patterns
Chain-of-Thought, ReAct, Self-Ask, and Tree-of-Thought in TypeScript. Thought-action-observation cycles, LangChain agent scratchpads, and prompt injection defense middleware.
CoTReActSelf-AskInjection Defense
A-02 // Retrieval
RAG + KAG Integration
GraphRAG with Milvus combines vector search and knowledge graph traversal. Entity linking, mutual-indexing, relationship traversal, and hybrid pipelines for legal, research, and support.
KAGGraphRAGMilvusKnowledge Graphs
A-03 // Multimodal
Multimodal AI Development
Text, image, audio, and video via ModelFusion TypeScript abstraction. Any-to-any architectures, Weaviate integration, Reka and Gemini comparison, and on-device deployment.
ModelFusionWeaviateGeminiVision
A-04 // Patterns
Advanced Patterns for AI Applications
TypeAI toolkit for type-safe AI functions, generics and higher-order functions for reusable AI components, robust retry mechanisms, and caching strategies for LLM responses.
TypeAIGenericsCachingRetry Logic
A-05 // Enterprise
Enterprise-Grade AI Systems
Scalable microservices, auth for AI endpoints, ModelFusion observability hooks, monitoring dashboards, and serverless deployment on AWS Lambda, GCP, and Azure with CI/CD pipelines.
MicroservicesAuthObservabilityServerless
A-06 // UI Patterns
Prompt Engineering UI Patterns
Production prompt-centric UI in React and TypeScript: PromptTemplateForm, StreamingHandler, Zod-validated JSON prompts, self-reflection loops, A/B testing, and version control interfaces.
ReactZustandStreaming UIZod
A-07 // Agents
AI Agents & Autonomous Systems
ReAct agents with multi-tool state, LangGraph useStream hook, multi-tiered memory systems (short-term buffers + long-term vector stores), and domain-specialised multi-agent protocols.
LangGraphMulti-AgentMemoryReAct
A-08 // Capstone
Final Project — Capstone II
Build a multimodal RAG+KAG system, an autonomous ReAct agent suite, an enterprise AI application with full observability, or a prompt engineering platform with version control and collaboration.
CapstoneRAG+KAGAgentsEnterprise
Complete Schedule

All 16 Modules
In Sequence Get Certified

F-01
Fundamentals for AI EngineersTypeScript · Async Patterns · Zod · Express
Foundation
F-02
Foundations of Generative AILLM Architecture · Embeddings · Prompt Engineering · SDK Overview
Concepts
F-03
Working with LLMs using TypeScriptMulti-SDK · Streaming · Function Calling · Safety
Integration
F-04
Retrieval-Augmented Generation (RAG)Vector DBs · Chunking · LangChain · Mastra
Retrieval
F-05
AI Frameworks & Agent DevelopmentMastra · VoltAgent · LLM-EXE · Memory & Tools
Agentic
F-06
Building Real-World GenAI Web AppsReact · NestJS · LangChain · Deployment
Applications
F-07
Ethics, Evaluation & SecurityBias · Hallucination · EU AI Act · Compliance
Governance
F-08
Capstone I — Foundations BuildRAG · Agents · Multimodal · Live Presentation
Capstone I
Track 2 — GenAI Architecture Certificate
A-01
Advanced Prompt Engineering PatternsCoT · ReAct · Self-Ask · Prompt Injection Defense
Reasoning
A-02
RAG + KAG IntegrationGraphRAG · Milvus · Entity Linking · Knowledge Graphs
Retrieval
A-03
Multimodal AI DevelopmentModelFusion · Weaviate · Vision · Audio · On-Device
Multimodal
A-04
Advanced Patterns for AI ApplicationsTypeAI · Generics · Caching · Retry Logic
Patterns
A-05
Enterprise-Grade AI SystemsMicroservices · Auth · Observability · Serverless CI/CD
Enterprise
A-06
Prompt Engineering UI PatternsReact · Zustand · Streaming UI · Version Control
UI/UX
A-07
AI Agents & Autonomous SystemsLangGraph · Multi-Agent · Memory · Domain Specialisation
Agentic
A-08
Capstone II — Advanced BuildRAG+KAG · Autonomous Agents · Enterprise Deploy
Capstone II
Program Design

Why the
Complete Path

⌥
True Continuity
Track 2 is not a repeat — it assumes everything from Track 1 and advances immediately. No recap padding. Every module opens where the last one closed.
▲
TS End-to-End
Both tracks are TypeScript native. Patterns, idioms, and tooling stay consistent across all 16 modules — your investment in the language compounds throughout.
◈
Two Capstones
Two build-and-present moments — one at Foundation level, one at Architecture level. You leave with two portfolio projects, not one.
⬡
From Demo to Deploy
Track 1 gets you shipping. Track 2 gets you scaling. The complete path covers both — the gap between "it works locally" and "it runs in production" is the curriculum.
Enroll

Start at Foundations.
Graduate at Architecture.

The complete GenAI program takes your team from first TypeScript setup through enterprise-grade autonomous AI systems — in one continuous, TypeScript-native learning path. Sixteen modules. Two certificates. Zero filler.

Enroll Your Team Get Certified