Cohort-2024-03

Gain a thorough understanding of the World of Generative AI with a deep understanding on how to build your own applications with Agents

Hamza Farooq

Founder | Ex-Google |
Instructor Stanford Continuing Studies & Adjunct UCLA

Building GenAI Agents for Enterprise Use

Google

University of Minnesota

Coursera

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 &amp; ML Engineers seeking to build custom RAG pipelines, agents, and fine-tuned models Product &amp; Tech Leaders who want to design scalable, safe, and responsible GenAI systems Anyone who wants to learn how Gen AI can be used 📚 Course ModulesModule 1: The World of Generative AI — Why Leaders Must Understand ItUnderstand 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 &amp; RAG Building BlocksGet 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 GuardrailsMove from MVP to enterprise: add semantic caching, optimize inference, and enforce safety with tools like LlamaGuard. Module 4: Agents and Their Ecosystem — Vibe Coding &amp; Vertical AI AgentsWhat 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 &amp; Knowledge GraphsLearn 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 WeekWorkshop 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 DayPresent your fully built, working system to the cohort. From agent demos to enterprise RAG deployments — this is where theory meets execution. 💡 Why This Course MattersThe 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.

What can Agents do for me?

You are intrigued about LLMs and would like to build applications powered by LLMs

You are ready to deploy your own SOTA AI Models and like to see how they work

You want to go beyond Jupyter Notebook and develop batch or real-time prediction

Who is this course for

What you’ll get out of this course

Collect and preprocess data for large language models

Train and fine-tune pre-trained large language models for specific tasks

Evaluate the performance of large language models and select appropriate metrics

Deploy large language models in real-world applications using APIs and Huggingface

Understand ethical considerations involved in working with large language models, such as avoiding bias and ensuring transparency

<ol><li>Introduction to NLP: covers what NLP is, its history, applications and challenges.</li><li>NLP Techniques: covers common techniques such as tokenization, part-of-speech tagging, named entity recognition and sentiment analysis with examples of their use.</li><li>NLP Tools: introduces popular NLP tools such as NLTK, spaCy with examples of how to use them </li></ol>

Introduction to Natural Language Processing

<ol><li>Transformers Foundational Knowledge: covers fundamental concepts of transformers, including self-attention, multi-head attention, and positional encoding.</li><li>Introduction to Fundamental Concepts of ML System Design: covers the basics of designing machine learning systems, including data collection and preprocessing, model selection and training</li></ol>

Foundational Knowledge of Transformers & ML System Design

<ol><li>Introduction to Information Retrieval Systems: covers the basic concepts and goals of information retrieval systems and their importance in various applications.</li><li>FAISS: introduces Facebook's AI Similarity Search (FAISS) library, a popular open-source library for efficient similarity search and clustering of dense vectors, and explains how it works.</li></ol>

Retrieval Systems

<ol><li>Deployment on a Serverless Inference: discusses the benefits of serverless computing and how to deploy the semantic search model on a serverless platform like Huggingface</li><li>Preprocessing of Hotel Data</li><li>Evaluation of the Model: discusses the different evaluation metrics used for semantic search models and how to measure the performance of the model</li></ol>

Building a search engine from bare bones and deploying it on Huggingface using server-less inference

<ol><li>Introduction to Knowledge Graph: covers the basics of knowledge graphs, including their architecture, data modeling, and how they are used in real-world applications like search engines and recommendation systems.</li><li>Generative AI: introduces the concept of generative AI and how it is used to generate new data, such as text, images, and music. </li></ol>

Knowledge Graph, Generative AI, Alpaca,Llama and Dolly 2.0 and World of langchain on larger corpus of Data

<ul><li>Understand the difference between prompt engineering and fine tuning</li><li>Introducing bits and bytes</li><li>Fine tuning GPT3</li></ul>

Fine tuning Models using PeFT and QLoRa

Teams get to present their learnings through a capstone project

Demo Day

Course syllabus

Data Scientist & Career Coach at Data Sistah

What people are saying

Excited to have you here

We will go through each module during this class

Saturday: Module Teaching

Students will spend time building projects with their team members or individually

Weekly projects

Course schedule

This course builds on live workshops and hands-on projects

Active hands-on learning

You’ll be interacting with other learners through breakout rooms and project teams

Interactive and project-based

Join a community of like-minded people who want to learn and grow alongside you

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