Program Objectives

  • Unlock Next-Level GenAi Skills

    Explore advanced GenAi methods such as prompt engineering, TAG, RAG, Langchain, and Agent Architectures

  • Imagine New Business Applications

    Leverage the power of GenAi to transform your business by imagining innovative solutions tailored to your unique opportunities

  • Lead the Transformation

    Build the confidence in GenAi to spearhead digital transformation in your organization

Explore the Foundations of GenAi and its Direct Business Application

Offered by UC Irvine’s Leadership Development Institute, Generative AI for Business Application is a self-paced, fully on-demand, digital program. This course features a curriculum that provides both theoretical and practical knowledge in generative AI. Taught by a unique blend of top academic and industry professionals, participants will gain the necessary insights to begin imagining applications for business.The program delves into the world of large language models (LLMs), and explores pathways for new accelerated value creation. Upon completion participants will receive an Official Certificate in Generative AI by UC Irvine's Paul Merage School of Business - Leadership Development Institute.

Exclusive Program Experience

Designed to meet the needs of today's fast-paced environment. Learn on your pace and become part of a larger community of learners

  • 100% On-Demand: Learn at the speed that suits you with our self-paced program

  • Advanced AI Certificate: UC Irvine Paul Merage School of Business Official Certificate Granted upon Completion

  • UC Irvine Faculty: Get exclusive knowledge from top academic minds in the field

Program Curriculum

On-Demand, Self-Paced Program Experience

    1. Module One Introduction

    2. Session One: What is AI?

    3. Session Two: Prompt Engineering, RAG + TAG

    4. Session Three: Opening the GenAI Blackbox (Part 1)

    5. Session Four: Opening the GenAI Blackbox (Part 2)

    6. Session Five: Economics of Generative AI

    7. Session Six: Use Cases for Generative AI

    8. Module One Final Quiz

    9. Extra Content 1: What Is Generative AI?

    10. Extra Content 2: AI Transforming the World of Work

    11. Extra Content 3: What is Coming After GPT-4o?

    1. Module Two Introduction

    2. Session One: Advanced Prompt Engineering

    3. Session Two: Prompt Design

    4. Session Three: Advanced Techniques

    5. Session Four: Tree of Thought Prompting

    6. Session Five: Prompt Tunning & Refinement

    7. Session Six: Recap

    8. Module Two Final Quiz

    9. Extra Content 1: 4 Methods of Prompt Engineering

    10. Extra Content 2: Use AI as a Creative or Expert Partner

    11. Extra Content 3: Discover Prompt Engineering

    1. Module Three Introduction

    2. Session One: Taxonomy Augmented Generation (TAG)

    3. Session Two: LLM with Unsupervised and Supervised Classification

    4. Session Three: LLM and Supervised Classification with Description

    5. Session Four: LLM and Supervised Classification Multi-Shot

    6. Session Five: LLM with Taxonomy Augmented Generation (TAG)

    7. Session Six: LLM with TAG Summary

    8. Module Three Final Quiz

    9. Extra Content 1: Introduction to Large Language Models

    10. Extra Content 2: Context Optimization vs LLM Optimization

    11. Extra Content 3: Supervised vs Unsupervised Learning

    1. Module Four Introduction

    2. Session One: Challenges with LLMs

    3. Session Two: Internal vs External Models

    4. Session Three: Building a RAG System

    5. Session Four: RAG Use Cases

    6. Session Five: Data Extraction, Chunkification & Embedding

    7. Session Six: Applying Embeddings & Vector Databases

    8. Module Four Final Quiz

    9. Extra Content 1: What is Retrieval-Augmented Generation

    10. Extra Content 2: How to Use Retrieval Augmented Generation (RAG)

    11. Extra Content 3: Using RAG Expansion to Improve Model Seed & Accuracy

    1. Module Five Introduction

    2. Session One: AI Application & Key Components

    3. Session Two: AI Governance Framework

    4. Session Three: LLM Testing Framework

    5. Session Four: LLM Model Evaluation and Measurements

    6. Session Five: Collaboration Strategies

    7. Session Six: AI Governance Summary

    8. Module Five Final Quiz

    9. Extra Content 1: Introduction to Responsible AI

    10. Extra Content 2: How Responsible AI Can Prepare You for AI Regulations

    11. Extra Content 3: Ethics of AI Challenges and Governance

    1. Module Six Introduction

    2. Session One: Building GenAI Solutions with TAG and RAG

    3. Session Two: GenAI Integration with Third Party Systems

    4. Session Three: Combining Generative and Predictive AI

    5. Session Four: Full Stack AI Frameworks

    6. Session Five: Agentic Framework

    7. Session Six: Course Summary

    8. Module Six Final Quiz

    9. Extra Content 1: The Rise of AI Agents and Agentic Reasoning

    10. Extra Content 2: Transform Your Business with Agentic AI

    11. Extra Content 3: The Truth on AI Agents with Marc Benioff

About this Program

  • 66 lessons
  • 10 hours of video content
  • On-Demand (Self-Paced)
  • $1,650 (USD)
  • UC Irvine AI Certificate

Module One Intro Preview

This foundational module opens the door to the fascinating world of Large Language Models, or LLMs, and their transformative impact on modern industries. In this module, participants will gain an essential understanding of how generative AI and LLMs function—learning the principles that underpin their remarkable ability to process language, generate insights, and drive decision-making.

Meet Your World-Class Faculty

Leading Global Experts in the Field of Information Systems, Data and Generative AI

Vidyanand (VC) Choudhary, Ph.D.

Associate Professor Information Systems, UCI

Vidyanand ("VC") Choudhary is a professor of Information Systems and Director of International Programs, recognized as an expert in competitive strategy for technology products and AI. His research spans the economics of information systems, AI’s business impact, creativity enhancement, recommender systems, corporate governance, and pricing strategies for cloud and SaaS products, with publications in top journals like Management Science and MIS Quarterly. He teaches courses on data management, AI, machine learning, and global business strategy, and has held leadership roles including Senior Associate Dean, Associate Dean of Undergraduate Programs, and Faculty Chair.

Vibhanshu (Vibs) Abhishek, Ph.D.

Associate Professor, UCI

Vibhanshu Abhishek is an Associate Professor of Information Systems at UC Irvine’s Paul Merage School of Business, where his research explores how emerging technologies shape consumer behavior, business strategies, and market structures, with a focus on multi-channel retail, advertising, pricing, e-commerce dynamics, and shared urban mobility. His work, published in top journals like Operations Research and Marketing Science, has earned accolades such as the Google Faculty Research Award and the ISS Nunamaker-Chen Dissertation Award, and has been featured in outlets like the NY Times and Forbes. With a PhD from the Wharton School and industry experience with firms like McKinsey & Co. and Adobe, he advises hi-tech startups and previously served as an Assistant Professor at Carnegie Mellon University.

Neena Sathi

Principal, Applied AI Institute

Neena Sathi is a Principal at Applied AI Institute, specializing in developing analytical and cognitive solutions in areas like Generative AI, Conversational AI, and Advanced Machine Learning, with over 30 years of consulting experience. Previously, she held director roles at KPMG, IBM, and Level3/CenturyLink, focusing on cognitive and automation solutions to enhance customer experience, back-office operations, and risk compliance. A Master Certified Integration Architect and PMP, she drives cognitive solution development from prototype to production and helps clients implement Cognitive Journey maps and pilot systems. Sathi has published extensively in journals like AAAI and IEEE and holds certifications in various cloud and cognitive technologies.

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