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.

This course is roughly divided in two parts:

1. No Code tools for building AI Agents

2. Low code approaches for building more complex Agents

You've likely experienced this firsthand: vendors promising AI solutions that will transform your business overnight, countless products with overlapping capabilities, and the nagging question: "Which of these actually solves our unique problems?"

Our startup has worked with organizations across fintech, supply chain, consulting, and manufacturing sectors, and we've consistently encountered the same challenge: businesses know AI matters, but struggle to identify concrete use cases that deliver measurable ROI.

This course addresses precisely that gap—helping you cut through the noise to identify, build, and deploy GenAI applications that create actual business value.

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

Designed for Business Leaders, Not Developers

What sets this course apart is our relentless focus on the "what" rather than just the "how." While many courses dive directly into technical implementation, we prioritize use case identification, business value assessment, and strategic deployment considerations that matter to non-technical leaders.

You don't need a programming background to succeed here. For business professionals who want to understand the capabilities without getting lost in the code, we've designed an experience that emphasizes concepts, applications, and outcomes.

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 Gen AI 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

This course is designed for:

- Product Managers looking to integrate GenAI into their roadmaps with clarity and confidence

- Technical Leaders and Architects who want to build scalable and safe GenAI systems

- Startup Founders & Innovation Teams aiming to create competitive GenAI-powered products

- Data Scientists & ML Engineers who want to go beyond notebooks and deploy impactful GenAI apps

- Consultants & Enterprise Strategists exploring GenAI adoption and implementation strategies for clients

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: Building Blocks of no Code Agents

Why do most enterprise search and Agentic solutions disappoint users? Discover the fundamental components that transform basic document search into contextual intelligence systems. Get hands-on with embeddings, chunking strategies, and the architecture of RAG systems that actually return relevant information.

Connect RAG to Agents to interact with end users

Module 3: Enterprise RAG with Guardrails—Moving Beyond Prototypes

Why do systems that work in demos fail in production? Learn how to transform proof-of-concepts into enterprise-grade solutions with semantic caching, optimized inference, and essential safety controls. Implement trustworthy systems that match your organization's risk tolerance and compliance requirements.

Module 4: Agents and Their Ecosystem — Vertical AI Agents

What are agents really? Go beyond CrewAI and Autogen to build your own agent orchestration framework using AgentPro. Focus on vertical agents like Data Analyst Bots, Research Assistants, and more.

Module 5: Teaching LLMs Your Organization's Language Through Fine-Tuning

Why do generalist models struggle with your industry's terminology? Learn practical approaches to adapting models to your domain's vocabulary, processes, and knowledge structures. Implement LoRA fine-tuning and knowledge graph integration techniques that ground AI in your organizational context.

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 Is Different?

The GenAI landscape is cluttered with tools, frameworks, and platforms—each promising to be the silver bullet. Our approach isn't about teaching you specific tools that will be outdated in six months. Instead, we focus on the enduring principles of identifying high-value use cases and building solutions that address actual business needs.

Our startup has guided organizations through the process of moving from AI curiosity to deployment, and we've distilled those lessons into this course.

You'll learn to look beyond the marketing hype to determine which problems in your organization are genuinely suited for Gen AI solutions.

This Course Delivers Results Where Others Don't

Unlike theoretical courses that leave you wondering how to apply concepts, or technical deep-dives that ignore business realities, this program bridges the gap between possibility and practicality.

We've designed every session to answer the question: "How do I use this to create actual value in my organization?"

Whether you're looking to enhance customer experiences, streamline operations, or unlock insights from unstructured data, you'll complete this course with concrete tools to transform GenAI from a buzzword into a business advantage.

✅ What You'll Get (Outcomes, Action-Oriented)

By the end of this course, you’ll be able to:

🧠 Understand the GenAI Landscape: Cut through the noise and get a clear grasp of how LLMs, RAG, and Agents fit into real-world enterprise workflows.

🛠️ Build Production-Ready AI Agents: Learn how to design and deploy AI Agents that go beyond simple Python scripts — handling reasoning, memory, retrieval, and tool use.

💼 Deliver Business Impact: Map Agent use-cases to measurable ROI — from automating internal knowledge retrieval to customer service, market analysis, and more.

🧪 Customize & Scale Your Solutions: Fine-tune domain-specific models, design feedback loops, and deploy with guardrails.

🚀 Capstone + Demo Day: Work on a real-world Agent project and showcase it to a private network of peers, builders, and mentors.