We’re living through one of the most transformative periods in the history of computing — and Generative AI is at the heart of it. From content creation and personalized customer support to autonomous decision-making and intelligent search, GenAI is rapidly redefining how businesses operate, how knowledge is accessed, and how software is built.

But for all its promise, the GenAI ecosystem is also overwhelming. The flood of tools, frameworks, benchmarks, and buzzwords can make it difficult to understand what truly matters — and even harder to translate that understanding into real, functional systems.

That’s where this course comes in.

Building GenAI Agents for Enterprise Use is designed to give you a laser-focused and in-depth view of real-world GenAI applications.

You’ll move beyond demos and prototypes and gain the skills to architect production-grade Retrieval-Augmented Generation (RAG) systems, build autonomous multi-agent workflows, and deploy LLM-powered solutions that actually work and with impact.

This course is one of the top-rated Gen AI Course on Maven, with over 1000 professionals trained from companies across tech, finance, government, and healthcare.

It has been successfully offered at Stanford Continuing Studies and the UCLA Anderson School of Management for their Master’s in Business Analytics programs.

Designed for executive leaders, data scientists, machine learning engineers, and product managers, the course demystifies the GenAI landscape by blending deep technical concepts with practical enterprise deployment strategies.

This is not another LangChain how-to or framework tour. Instead, this course teaches you to build modern GenAI systems from first principles, grounded in real-world constraints like scale, guardrails, multi-agent workflows, and domain-specific adaptation.

🎯 Who This Course Is For

Executive Leaders looking to understand the real technical backbone of GenAI beyond the buzzwords

Data Scientists & ML Engineers seeking to build custom RAG pipelines, agents, and fine-tuned models

Product & Tech Leaders who want to design scalable, safe, and responsible GenAI systems

Anyone who wants to learn how Gen AI can be used

📚 Course Modules

Module 1: The World of Generative AI — Why Leaders Must Understand It

Understand the GenAI revolution and what it means for industries, infrastructure, teams, and the future of software. We break down the LLM ecosystem, the commoditization of models, and the real moats: data and architecture.

Module 2: Search Engines & RAG Building Blocks

Get hands-on with the fundamentals: embeddings, chunking, semantic search, hybrid search, and how to build RAG (Retrieval-Augmented Generation) pipelines using open-source tools.

Module 3: Enterprise RAG with Guardrails

Move from MVP to enterprise: add semantic caching, optimize inference, and enforce safety with tools like LlamaGuard.

Module 4: Agents and Their Ecosystem — Vibe Coding & Vertical AI Agents

What are agents really? Go beyond CrewAI and Autogen to build your own agent orchestration framework using AgentPro. Learn Vibe Coding — our term for creatively building agents that are not flashy but actually useful. Focus on vertical agents like Data Analyst Bots, Research Assistants, and more.

Module 5: Fine-Tuning, Continual Pretraining & Knowledge Graphs

Learn how to adapt and improve your models using LoRA, and continual pretraining pipelines. Explore how Knowledge Graphs can structure and ground your agent interactions.

Module 6: Capstone Discussion Week

Workshop your final project ideas, get peer and instructor feedback, and finalize your architecture and approach for your custom RAG or Agent system.

Module 7: Demo Day

Present your fully built, working system to the cohort. From agent demos to enterprise RAG deployments — this is where theory meets execution.

💡 Why This Course Matters

The future of enterprise AI is not just about plugging into APIs. It's about understanding how to build systems that are safe, scalable, and strategic.

This course equips you to become not just a user of GenAI, but a builder, architect, and leader in its evolution.