Application closes on
16th Apr 2026
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Application closes 16th Apr 2026
Curated for professionals from diverse backgrounds, the research-backed curriculum ensures that participants can build and deploy intelligent agents regardless of their technical starting point.
This program offers learners the flexibility to choose between two distinct tracks at the outset of the program: a coding-based track (Python-focused) and a no-code, tools-based track.
LEARNING OUTCOMES
Build Agentic AI workflows to solve business problems and drive growth
Navigate the AI landscape and understand foundational concepts to address common business challenges
Apply and evaluate LLM and prompt engineering techniques to optimize performance, and ensure prompt stability
Build intelligent, context-aware single-agent systems to automate workflows and improve operational efficiency
Implement planning and reasoning strategies that enable autonomous agents to solve complex business problems
Design and evaluate scalable, transparent multi-agent ecosystems to ensure reliable enterprise AI solutions
Implement and evaluate RAG systems to enhance accuracy, contextual relevance, and business productivity
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KEY PROGRAM HIGHLIGHTS
Learn from recorded lectures and monthly live masterclasses by Texas McCombs faculty, and live, mentor-led sessions where industry experts present real-world case studies
Choose between a Python-based coding track or a no-code, tools-based track, and complete hands-on components using aligned technologies
Build industry-ready skills for creating intelligent Agentic AI systems using industry-relevant tools, projects, and real-world case studies across sectors
Get personalized assistance from a dedicated program manager, academic support through the Great Learning community, project discussion forums, and peer groups
Develop an industry-ready portfolio that showcases your mastery of skills and tools
Upon program completion, earn a globally recognized certificate of completion and Continuing Education Units (CEUs) from Texas McCombs
Skills you will learn
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Professionals across career stages seeking a flexible learning track to build Agentic AI systems.
Knowledge Professionals
Looking to develop practical, industry-ready skills in Agentic AI and Generative AI to automate and optimize workflows.
Business and Technology Experts
Seeking a strong foundation in Generative AI to expand their knowledge in designing intelligent Agentic AI systems.
Functional Professionals and Managers
Looking to develop industry-ready skills to build solutions that automate and optimize workflows within their organizations.
Implementation Strategists
Designing end-to-end pilots that account for clinical workflow mapping, stakeholder constraints, and safe deployment.
Aspiring AI Practitioners
Aiming to build technical expertise in GenAI and contribute to projects using Agentic AI for process automation and intelligence.
Technical Leaders, Decision-Makers, and Innovators
Driving GenAI adoption in the workplace, aiming to guide their teams in translating business workflows into Agentic AI solutions.
Our pedagogy is designed to ensure career growth and transformation
Learn critical concepts through live masterclasses and recorded video lectures
Clarify your doubts and gain practical skills during weekly live sessions with industry experts
Work on projects to apply the concepts & tools learnt in the module
Our dedicated program managers will support you through your learning journey
AI Agents and GenAI with On-Campus Immersion
In the 3-day immersive on-campus program, you will:
Reach our to your Program Advisor for more details
Designed by faculty from Texas McCombs, the curriculum offers a comprehensive overview of AI agents, from the fundamentals of GenAI, large language models, and retrieval-augmented generation to building intelligent, scalable systems that automate business workflows and enhance decision-making.
3
Hands-On Projects
15+
Case Studies
15+
Tools and Technologies
This module introduces learners to the AI landscape by exploring key concepts, technologies, and business applications of AI, Generative AI, and Agentic AI. It also provides foundational knowledge of the tools and environments used throughout the program, enabling learners to begin building AI-powered solutions using both code- and no-code approaches.
This module provides an overview of the Generative AI and Agentic AI landscape, exploring the critical distinctions between generative and discriminative AI, their applications, and bias and hallucination associated with modern AI systems.
This module builds on a fundamental understanding of LLMs by tackling the challenge of prompt stability, optimizing prompts for consistent performance, providing a rigorous framework for LLM evaluation via LLM-as-a-Judge, and curating gold-standard datasets for human evaluation. The module also covers Retrieval-Augmented Generation (RAG), exploring data chunking, embeddings, and vector databases to ground models in external knowledge, to build and evaluate context-aware, reliable Generative AI solutions.
This module focuses on designing and implementing Agentic AI systems for complex business applications. Learners begin by examining responsible AI practices and security considerations for deploying LLM-based solutions. The module then explores the architecture of AI agents, including how tools, memory, and reasoning strategies enable autonomous task execution. Building on this foundation, learners design both single-agent and multi-agent systems capable of collaboration and distributed problem-solving. The module concludes with evaluation techniques and human-in-the-loop approaches to ensure reliability, performance, and governance in Agentic AI solutions.
This module will help you explore how to solve business problems by examining the capabilities of text-to-image and image-to-text Generative AI tools like DALL·E through business use cases and by exploring the speech recognition capabilities of audio-to-text Generative AI tools like Whisper through business use cases.
Engage in hands-on projects and 15+ real-world case studies using emerging tools and technologies
Project
Description
CUSTOMER SUPPORT | Improve customer experience and operational efficiency by leveraging NLP and LLM-based automation to classify support tickets, tag key issues, prioritize them using sentiment signals, and generate automated first responses for faster and more effective customer support.
Skills you will learn
Project
Description
FINANCE | Aid Financial Analysts of an organization to extract key information from long financial documents like annual reports effectively using Retrieval-Augmented Generation (RAG), thereby increasing efficiency in making key financial decisions.
Skills you will learn
Project
Description
LOGISTICS AND SUPPLY CHAIN | Improve last-mile logistics efficiency by implementing a multi-agent AI system that detects delivery exceptions from operational logs, applies policy-based reasoning to determine optimal resolution actions, generates personalized customer communications, and escalates complex cases while maintaining full auditability.
Skills you will learn
Case Study
Description
RETAIL | Enable dynamic, context-aware interactions that assist customers with product queries and order tracking by developing a retail chatbot using a multi-agent system, improving the overall shopping experience.
Skills you will learn
Foundational and advanced tools for Agentic AI to solve complex business challenges
n8n
Python
LangChain
LangGraph
LangSmith
Google Colab
OpenAI APIs
NotebookLM
Earn a globally recognized credential from a top U.S. university and showcase it to your network
* Image for illustration only. Certificate subject to change.
Learn from the top, world-renowned faculty from Texas McCombs
Faculty Director, McCombs School of Business, The University of Texas at Austin
Faculty Director, Center for Analytics and Transformative Technologies
21+ years' experience in AI, ML, Deep Learning, and NLP.
Clinical Assistant Professor, McCombs School of Business, The University of Texas at Austin
Ph.D. in Information, Risk, and Operations Management
15+ years of experience in financial engineering
Interact with dedicated mentors who are practitioners and experts in Agentic AI
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The course fee is USD 3,450
Navigate the AI landscape and understand foundational concepts to address common business challenges
Apply GenAI, Large Language Models, and Retrieval-Augmented Generation to enhance business productivity
Build intelligent, context-aware single-agent systems to automate workflows and improve operational efficiency
Implement planning and reasoning strategies that enable autonomous agents to solve complex business problems
Applications close once the required number of participants enroll. Apply early to secure your spot
Register by completing the online application form.
A panel from Great Learning will review your application to determine your fit for the program.
Receive an offer for a seat in the upcoming cohort of the program after a final review.
The McCombs School of Business at the University of Texas at Austin is collaborating with online education provider Great Learning to offer the Post Graduate Program in AI Agents and Generative AI for Business Applications. Great Learning collaborates with institutions to manage enrollments (including all payment services and invoicing), technology, and participant support.
Application closes
16th Apr 2026
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