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Application closes 10th Nov 2025

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Program Outcomes

Elevate your career with AI

Build Agentic AI workflows to solve business problems and drive growth

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    Navigate the AI landscape and understand foundational concepts to address business challenges across functions

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    Apply GenAI, large language models, and Retrieval-Augmented Generation to enhance business productivity

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    Develop intelligent, context-aware single-agent systems to automate workflows and drive operational efficiency

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    Solve business problems with planning and reasoning strategies, and scalable, secure multi-agent ecosystem

Earn a certificate of completion from Texas McCombs

  • #1 (U.S., Big Data Management) in MS Business Analytic

    #1 (U.S., Big Data Management) in MS Business Analytic

    Eduniversal (2025)

  • #6 Analytics

    #6 Analytics

    U.S. News & World Report (2025)

  • #6 Business Programs

    #6 Business Programs

    U.S. News & World Report (2025)

  • #7 in MS - Business Analytics

    #7 in MS - Business Analytics

    QS World University Rankings (2022)

  • #7 in MS Business Analytics

    #7 in MS Business Analytics

    The Financial Engineer Times (2025)

  • #3 in Information Systems Graduate Programs

    #3 in Information Systems Graduate Programs

    U.S. News & World Report (April 2025)

  • #7 Public University in the U.S.

    #7 Public University in the U.S.

    U.S. News & World Report, 2026

  • #6 in Executive Education - Custom Programs

    #6 in Executive Education - Custom Programs

    Financial Times, 2022

Key program highlights

Why choose this program

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    Learn from top faculty

    Learn from recorded lectures and monthly live masterclasses by Texas McCombs faculty

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    Live mentored learning sessions

    Participate in interactive, mentor-led sessions where industry experts present real-world case studies, providing deep insights into AI applications in business

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    Hands-on learning

    Build industry-ready skills for creating intelligent Agentic AI systems using industry-relevant tools, projects, and real-world case studies across sectors

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    Learning support

    Get personalized assistance from a dedicated program manager, academic support through the Great Learning community, project discussion forums, and peer groups

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    Create a compelling e-portfolio

    Develop an industry-ready portfolio that showcases your mastery of skills and tools

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    Earn recognized credentials

    Upon program completion, earn a globally recognized certificate of completion from the McCombs School of Business at The University of Texas at Austin

Skills you will learn

AGENTIC AI

GENERATIVE AI

LARGE LANGUAGE MODELS

PROMPT ENGINEERING

RAG

AGENTIC RAG

MCP FRAMEWORK

MULTI-AGENT SYSTEMS

RESPONSIBLE AI

AGENTIC AI

GENERATIVE AI

LARGE LANGUAGE MODELS

PROMPT ENGINEERING

RAG

AGENTIC RAG

MCP FRAMEWORK

MULTI-AGENT SYSTEMS

RESPONSIBLE AI

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  • Overview
  • Learning Journey
  • Curriculum
  • Projects
  • Tools
  • Certificate
  • Faculty
  • Mentors
  • Fees
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This program is ideal for

Professionals across career stages looking to advance their knowledge and skill in building Agentic AI systems

  • Knowledge professionals

    Looking to develop practical, industry-ready skills in Agentic AI to automate and optimize workflows

  • Business and tech experts

    Seeking to expand their knowledge in designing intelligent agentic systems to enhance decision-making and operational efficiency

  • Aspiring AI practitioners

    Preparing to contribute effectively to projects involving Agentic AI for process automation and intelligence

  • Technical leaders

    Aiming to guide their teams in translating business workflows into Agentic AI workflows to drive innovation and transformation

Experience a unique learning journey

Our pedagogy is designed to ensure career growth and transformation

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    Learn from world-renowned faculty

    Learn critical concepts through live masterclasses and recorded video lectures

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    Engage with your mentors

    Clarify your doubts and gain practical skills during weekly live sessions with industry experts

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    Work on hands-on projects

    Work on projects to apply the concepts & tools learnt in the module

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    Get personalized assistance

    Our dedicated program managers will support you through your learning journey

Comprehensive curriculum

Designed by Texas McCombs faculty, this curriculum offers a hands-on foundation in AI Agents. It covers Python, GenAI, Large Language Models, and Retrieval-Augmented Generation. Participants learn to build intelligent AI agents using tools, memory, planning, and reasoning, progressing to secure, scalable multi-agent systems for business application

PRE-WORK

This module will help learners navigate the AI landscape by identifying key problems and solution spaces, enabling businesses to leverage AI technologies effectively, and acquire fundamental programming skills in Python to build the necessary foundation to develop AI solutions to support business initiatives.

Introduction to AI Landscape

1. Introduction to key terminology (Artificial Intelligence, Machine Learning, Deep 2. Learning, Generative AI, Large Language Models, Agentic AI) 3. History and evolution of AI 4. Business problems and solution spaces across different industries

Python Foundations

1. Introduction to Python: overview and why industries prefer Python over other languages 2. Python environment: VS Code, Google Colab 3. Fundamental Python programming constructs: variables, data types, data structures (list, dictionary, tuple) 4. Conditional and looping statements, functions 5. OOP basics: classes, objects, inheritance

MODULE 01: AGENTIC AI FOUNDATIONS

This module focuses on building a strong foundation in Generative AI and Large Language Models by differentiating them from discriminative approaches, understanding how LLMs work and their enterprise applications, practicing prompt engineering with techniques and templates to improve reliability and scalability, and exploring Retrieval-Augmented Generation (RAG) and its key components to overcome the limitations of prompting and develop context-aware, enterprise-ready AI solutions.

Introduction to Generative AI and Large Language Models

1. Generative AI vs. Discriminative AI 2. Overview of LLMs 3. Interacting with Generative AI 4. Risks of Generative AI 5. Business applications of Generative AI

Prompt Engineering and Retrieval Augmented Generation

1. The need for Prompt Engineering 2. Common prompting techniques (Zero-shot, One-shot, Few-shot, Chain-of-Thought) 3. Best practices for crafting effective prompts 4. Reusable prompt templates 5. The need for RAG 6. Key components of RAG (data chunking, embeddings, vector store, retrieval, augmentation, generation)

Project Week

MODULE 02: BUSINESS APPLICATIONS WITH AGENTIC AI

This module focuses on understanding and developing AI agents, equipping learners with both foundational insights and advanced techniques in Agentic AI implementation. It begins with an introduction to AI agents, where you explore the basic concepts and frameworks that define intelligent agents. The module then delves into how tools and memory can be incorporated into agents to enhance their functionality and efficiency in task execution. Finally, it covers planning and reasoning, teaching you how agents can be programmed to make informed decisions and solve complex problems autonomously.

Introduction to AI Agents

1. The need for AI agents 2. Types of agents 3. Agent environments 4. Grounding and validation 5. Building simple AI agents with LangChain 6. Agentic RAG

Incorporating Tools and Memory in Agents

1. The need for external tools 2. Types of tools 3. The need for memory 4. Short-term vs Long-term memory 5. Introduction to MCP 6. Tool-based agents with MCP

Planning and Reasoning

1. The role of planning 2. Self-reflection 3. The role of reasoning 4. Multi-step reasoning 5. Task decomposition 6. Introduction to the ReAct framework

Learning Break

Project Week

MODULE 03: ADVANCED AGENTIC AI SOLUTIONS

This module explores advanced concepts in Agentic AI, starting with multi-agent systems, where learners examine the interaction and coordination between multiple AI agents to solve complex problems collaboratively. Next, the focus shifts to testing and evaluating agentic systems, providing insights into methodologies for assessing the performance, reliability, and effectiveness of AI agents in various scenarios. Finally, the module covers the crucial topic of securing agentic AI solutions, highlighting the importance of implementing robust security measures to protect AI systems from vulnerabilities and ensure safe deployment in real-world applications.

Multi-Agent Systems

1. The need for multi-agent systems (specialization and expertise, scalability and 2. parallel processing, security and fault tolerance) 3. Architecture of a multi-agent system 4. Designing a multi-agent system

Testing and Evaluation of Agentic Systems

1. Unit testing 2. Integration testing 3. System testing 4. Multi-agent testing 5. Evaluation metrics (accuracy, latency, robustness) 6. Grounding, validation, and truthfulness 7. Human-in-the-loop evaluation

Securing Agentic AI Solutions

1. Data security and privacy 2. Agent behavior security 3. Logging decision-making for transparency 4. Access control and identity 5. Regulatory compliance and ethical considerations 6. Deploying a single/multi-agent system as a web app

Project Week

SELF-PACED COURSE

Multimodal Agentic AI (Masterclass only)

This masterclass builds a foundational understanding of multimodal Agentic AI systems, focusing on how models integrate and align information across text, vision, and other modalities through cross-modal reasoning and attention. 1. Multimodal Foundation Models 2. cross-Modal Reasoning, Attention & Alignment

Work on hands-on projects and case studies

Engage in hands-on projects and 15+ real-world case studies using emerging tools and technologies

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    Hands-on projects

  • 15+

    Real-world case studies

  • 15+

    High-growth skills

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FINANCE

Company Financial Report Q&A Bot

Description

Help financial analysts of an organization extract key information from lengthy financial documents, such as annual reports, by effectively leveraging Retrieval-Augmented Generation (RAG). This improves efficiency in making key financial decisions.

Skills you will learn

  • Generative AI
  • Large Language Models
  • Prompt Engineering
  • Hugging Face
  • Retrieval-Augmented Generation
  • Vector Databases
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HEALTHCARE

Patient Support & Medical Info Agent

Description

Develop a healthcare assistant that aids patients in understanding health records, sourcing information from trusted medical knowledge bases, and maintaining context over multiple interactions.

Skills you will learn

  • Agentic AI
  • Large Language Models
  • Prompt Engineering
  • Hugging Face
  • LangChain
  • LangGraph
  • MCP
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LEGAL

Intelligent Document Processing System for Legal Firm

Description

Create a multi-agent AI system to automate the processing, analysis, and management of legal documents, enhancing workflow efficiency from intake to compliance verification.

Skills you will learn

  • Agentic AI
  • Large Language Models
  • Multi-Agent Systems
  • Workflow Automation
  • LangGraph
  • LangSmith
  • Human Feedback Loops
  • Legal Document Compliance
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FINANCE

Financial Research Analyst Agent

Description

Leverage AI agent capabilities to automate data analysis and insight generation, enhancing the speed and quality of investment decision-making.

Skills you will learn

  • AI Agents
  • Data Analysis
  • Investment Decision-Making
  • LangChain
  • Python
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TRAVEL AND TOURISM

Travel Agent Application

Description

Utilize Agentic AI to integrate tools and manage contexts, enabling the creation of personalized travel packages that enhance customer satisfaction and conversion rates.

Skills you will learn

  • Agentic AI
  • Context Management
  • MCP
  • Travel Automation
  • Python
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HEALTHCARE

Healthcare Startup Application

Description

Apply planning and reasoning in Agentic AI to automate patient intake and appointment scheduling, enhancing operational efficiency and patient satisfaction.

Skills you will learn

  • Agentic AI
  • Planning and Reasoning
  • Process Automation
  • Healthcare Operations
  • ReAct
  • LangGraph
  • Python
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TECHNOLOGY

Automated Software Development Application

Description

Implement multi-agent systems to collaborate on tasks such as analysis, coding, and deployment, thereby streamlining and accelerating the software development lifecycle.

Skills you will learn

  • Multi-Agent Systems
  • Workflow Automation
  • Software Development
  • LangGraph
  • Python
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CUSTOMER SERVICE

Quality Assurance for Customer Service Chatbot

Description

Conduct quality assurance on a customer service chatbot to ensure it delivers accurate, relevant, and brand-consistent responses while effectively handling diverse queries and optimizing overall performance.

Skills you will learn

  • Chatbot Testing
  • QA Methodologies
  • LangSmith
  • Human Feedback Loops
  • Performance Optimization
  • Python
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RETAIL

Retail Order Query Chatbot

Description

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

  • Agentic AI
  • Multi-Agent Systems
  • Chatbot Development
  • Context-Aware Interaction
  • Python
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HUMAN RESOURCES

HR Policy Query Bot

Description

Build a RAG-powered HR policy query bot leveraging vector databases and prompt engineering to deliver accurate, efficient, and reliable employee query resolution.

Skills you will learn

  • Retrieval-Augmented Generation (RAG)
  • Prompt Engineering
  • Vector Databases
  • Chatbot Development
  • Python

Learn in-demand AI tools and techniques

Foundational and advanced tools for Agentic AI to solve complex business challenges

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    Python

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    LangChain

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    LangGraph

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    MCP Framework

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    LangSmith

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    LangChain ReAct

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    OpenAI APIs

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    ChatGPT

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    Hugging Face

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    ChromaDB

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    Google Colab

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    Streamlit

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    Transformers

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    Pandas

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    FAISS

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    Sentence Transformers

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    Dynabench

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    Llama Cpp

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    Gemini

Earn a certificate of completion

Earn a globally recognized credential from a top U.S. university and showcase it to your network

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* Image for illustration only. Certificate subject to change.

Meet your faculty

Learn from the top, world-renowned faculty at The University of Texas at Austin

  • Dr. Kumar Muthuraman - Faculty Director

    Dr. Kumar Muthuraman

    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.

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  • Dr. Daniel A Mitchell - Faculty Director

    Dr. Daniel A Mitchell

    Associate Director, Center for Analytics and Transformative Technologies, McCombs School of Business, The University of Texas at Austin

    Research Director, Center for Analytics and Transformative Technologies

    15+ years of experience in financial engineering and quantitative finance.

    Know More
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Interact with our industry mentors

Interact with dedicated mentors who are practitioners and experts in Agentic AI

  • Kalle Bylin - Mentor

    Kalle Bylin

    Product Engineer
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  • Bhaskarjit Sarmah - Mentor

    Bhaskarjit Sarmah linkin icon

    Director BlackRock
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  • Tanya Glozman - Mentor

    Tanya Glozman linkin icon

    Applied Science - AI/ML, Apple
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  • Bridget Huang-Gregor - Mentor

    Bridget Huang-Gregor linkin icon

    Tech Lead Engineering , Capital One
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  • Vinicio Desola Jr - Mentor

    Vinicio Desola Jr

    Senior AI Engineer Newmark
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Course Fees

The course fee is 2,900 USD + GST

Invest in your career

  • benifits-icon

    Apply GenAI, large language models, and Retrieval-Augmented Generation to enhance business productivity

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    Develop intelligent, context-aware single-agent systems to automate workflows and drive operational efficiency

  • benifits-icon

    Design, evaluate, and secure multi-agent ecosystems for enterprise AI solutions

  • benifits-icon

    Solve business problems with planning and reasoning strategies, and scalable, secure multi-agent ecosystem

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Easy payment plans

Avail our EMI options & get financial assistance

  • discount available

    Upfront discount:2,900 USD 2,750 USD + GST

Third Party Credit Facilitators

Check out different payment options with third party credit facility providers

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*Subject to third party credit facility provider approval based on applicable regions & eligibility

Take the next step

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Application Closes: 10th Nov 2025

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Application Closes: 10th Nov 2025

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Admission process

Admissions close once the required number of participants enroll. Apply early to secure your spot

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    Fill the application form

    Register by completing the online application form.

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    Application screening

    A panel from Great Learning will review your application to determine your fit for the program.

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    Join the program

    Receive an offer for a seat in the upcoming cohort of the program after a final review

Eligibility Criteria

  • Designed for professionals at different stages of their careers.
  • Ideal for those looking to advance their knowledge and skills in building Agentic AI systems.

Limited seats available

Apply now to start building with AI

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Connect with our advisors and get your queries resolved

Speak with our expert +15127980680 or email to aiaba.utaustin@mygreatlearning.com

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