Solve Business Problems with Agentic AI

Post Graduate Program in AI Agents for Business Applications

Application closes on 23rd Apr 2026

Delivered in collaboration with Great Learning

Learn more about the course

Get details on syllabus, projects, tools, and more

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Post Graduate Program in AI Agents for Business Applications

Application closes 23rd Apr 2026

Program Outcomes

Elevate Your Career with AI

Build Agentic AI workflows to solve business problems and drive growth

Navigate the AI landscape and understand foundational concepts to address business challenges across functions
Apply GenAI, large language models, and Retrieval-Augmented Generation to enhance business productivity
Develop intelligent, context-aware single-agent systems to automate workflows and drive operational efficiency
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

Eduniversal (2025)
#6 Analytics

U.S. News & World Report (2025)
#6 Business Programs

U.S. News & World Report (2025)
#7 in MS - Business Analytics

QS World University Rankings (2022)
#7 in MS Business Analytics

The Financial Engineer Times (2025)
#3 in Information Systems Graduate Programs

U.S. News & World Report (April 2025)
#7 Public University in the U.S.

U.S. News & World Report, 2026
#6 in Executive Education - Custom Programs

Financial Times, 2022

Key program highlights

Why Choose This Program

Learn from renowned faculty and experts

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 to learn with or without code

Choose between a Python-based coding track or a no-code, tools-based track, and complete hands-on components using aligned technologies.
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
Learning support

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

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

This Program Is Ideal for

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 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

Learn from world-renowned faculty

Learn critical concepts through live masterclasses and recorded video lectures
Engage with your mentors

Clarify your doubts and gain practical skills during weekly live sessions with industry experts
Work on hands-on projects

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

Our dedicated program managers will support you through your learning journey

Unique learning journey

Weekly live sessions

Interactive classes for concept clarity, hands-on and Q&A with IIT Bombay faculty.
Peer-to-Peer Learning

Learn with a cohort - discuss and share ideas in class and in discussion forums.
Industry-Relevant Curriculum

Work on projects - apply concepts & tools to real use cases
Get personalized assistance

Our dedicated programme managers will support you whenever you need

On-Campus Immersion (Optional Paid Program)

AI Agents with On-Campus Immersion

In the 3-day immersive on-campus program, you will:

Connect with like-minded AI-professionals
Engage with world-class faculty
Learn first-hand from global industry experts
Earn 2.5 CEUs upon program completion

Reach our to your Program Advisor for more details

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

Code or No-Code

Flexible learning tracks
15+

Tools and techniques
2.5 CEUs

Upon program completion

PRE-WORK

This preparatory module is designed to help learners navigate the AI landscape by identifying key problem areas and solution opportunities. It enables participants to understand how businesses can effectively leverage AI technologies while building a foundational understanding of the tools and frameworks required to develop Agentic AI solutions that support strategic business initiatives.

Introduction to AI Landscape

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

Hands-On Tool Introduction and Setup

Code Tools 1. Introduction to Python 2. Environment setup: VS Code, Google Colab 3. Fundamental Python programming constructs: variables, data types, data structures (list, dictionary, tuple), conditional and looping statements, functions 4. OOP basics: classes, objects, inheritance No-Code Tools 1. Introduction to no-code tools 2. Environment setup: GL N8N Labs 3. Core functionality and UI overview

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, parallel processing, security and fault tolerance) 2. Architecture of a multi-agent system 3. 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

3

Hands-on projects
15+

Real-world case studies
15+

High-growth skills

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

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

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

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

Learn In-Demand AI Tools and Techniques

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

Python
LangChain
LangGraph
MCP Framework
LangSmith
LangChain ReAct
ChatGPT
Hugging Face
ChromaDB
Google Colab
Streamlit
Transformers
Pandas
FAISS
Sentence Transformers
Dynabench
Llama Cpp
Gemini
NotebookLM

Earn a certificate of completion

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.

Meet Your Faculty

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

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.

Know More

Interact With Our Industry Mentors

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

Kalle Bylin

Product Engineer, Workday
Bhaskarjit Sarmah

Head of AI Research, Domyn
Tanya Glozman

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

GenAI/ML Engineer at Amazon Web Services (AWS)
Vinicio Desola Jr

Senior AI Engineer Newmark

Course Fees

The course fee is USD 3,450

Invest in your career

Choose from two flexible tracks: a Python coding track or a no-code tools track with hands-on components
Apply GenAI, large language models, and Retrieval-Augmented Generation to enhance business productivity
Develop intelligent, context-aware single-agent systems to automate workflows and drive operational efficiency
Solve business problems with planning and reasoning strategies, and scalable, secure multi-agent ecosystem

Take the next step

00 : 00 : 00

Apply to the program now or schedule a call with a program advisor

Unlock exclusive course sneak peek

Application Closes: 23rd Apr 2026

Talk to our advisor for offers & course details

Admission Process

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

Fill the application form

Register by completing the online application form.
Application screening

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

Program Details

Curriculum, Projects, and Certificate

Eligibility and Admissions

Fee Details

Career-related Queries

Other Queries

Program Details

What is the Postgraduate Program in AI Agents for Business Applications?

This is a 12-week AI Agents certificate program for Business Applications, designed by the McCombs School of Business at The University of Texas at Austin. It equips professionals with the skills to architect, deploy, and govern intelligent AI agents and multi-agent systems to automate business workflows.

What is the format of the program?

This AI agents course is online and consists of recorded video lectures, 8+ live mentorship sessions with global industry experts, and monthly live masterclasses led by Texas McCombs faculty.

Is this an AI agent course with a certificate, and what does it include?

Yes, this is a comprehensive AI agents course with a certificate. Upon successful program completion, you will earn a globally recognized Certificate of Completion from the McCombs School of Business at The University of Texas at Austin, along with 2.5 Continuing Education Units (CEUs). Because it is a hands-on AI agent course with a certificate, the program also includes access to OpenAI APIs via GL Labs, a shareable e-Portfolio, and personalized feedback for all projects.

How long does it take to learn AI agents?

It takes 12 weeks (3 months) to complete this program and learn how to build AI agents. The structured curriculum progresses from Generative AI foundations to advanced multi-agent systems.

Who are the faculty members for this program?

The program is designed and delivered by renowned faculty from the McCombs School of Business, including Dr. Kumar Muthuraman and Dr. Daniel A. Mitchell.

Curriculum, Projects, and Certificate

What are the learning outcomes of this program?

After completing this AI agent training, you will be able to: • Navigate the AI landscape and understand foundational concepts to address common business challenges across marketing, sales, and operations • Apply Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to enhance business productivity • Implement planning and reasoning strategies to enable autonomous agents to break down tasks, adapt to changing scenarios, and solve complex business problems with AI-powered intelligent processes • Design, evaluate, and secure multi-agent systems that are scalable, transparent, and compliant for enterprise AI solutions • Develop intelligent, context-aware single-agent systems by integrating tools and memory to automate workflows and improve operational efficiency

Will I learn how to build AI agents in this program?

Yes. The AI agents course syllabus teaches you how to build AI agents. It equips professionals with the practical skills to architect, deploy, and govern intelligent AI agents and multi-agent systems.

What is included in the AI agents course curriculum?

This AI agents development course covers foundations in either Python or no-code tools (depending on your chosen track), Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG). You will then progress to building intelligent AI agents using tools, memory, planning, and reasoning before mastering secure and scalable multi-agent systems.

Do AI agent courses include hands-on projects?

Yes, this program includes three hands-on projects and over 15 real-world case studies. Please refer to the projects section for more information.

What are the required tools for building AI agents, and which frameworks for AI agents will I learn?

In this program, you will learn over 20 in-demand tools for building AI agents and advanced frameworks for AI agents, including Python, LangChain, LangGraph, the Model Context Protocol (MCP) framework, LangSmith, n8n, OpenAI APIs, Hugging Face, and ChromaDB.

Will I receive a certificate upon completion?

Yes. Upon successful program completion, you will earn a globally recognized Certificate of Completion from the McCombs School of Business at The University of Texas at Austin. You will also earn 2.5 Continuing Education Units (CEUs).

What is included in an AI agents certificate program?

Beyond the core curriculum, the program includes access to OpenAI APIs via GL Labs, a shareable e-Portfolio, personalized evaluation and feedback for all projects, and a dedicated Program Manager for personalized assistance.

Eligibility and Admissions

Who is this program for?

This program is for: • Knowledge professionals looking to develop practical, industry-ready skills in Agentic AI to automate and optimize workflows • Business and technology experts seeking to expand their knowledge in designing intelligent agentic systems to improve decision-making and operational efficiency • Aspiring AI practitioners preparing to contribute to projects involving Agentic AI for process automation and intelligence • Technical leaders aiming to guide teams in translating business workflows into Agentic AI workflows to drive innovation and transformation

Do I need coding experience to learn AI agents?

Not necessarily. The program's Flexible Learning Track allows you to choose between a Python-focused coding track or a no-code, tools-based track, making it accessible even if you don't have a programming background.

Fee Details

What is the program fee for learners in India?

The AI agent program fee is ₹1,50,000 + GST.

Career-related Queries

Is an AI agents certificate worth it for careers?

Yes, as businesses rapidly shift toward AI-powered architectures, there is a growing talent gap for professionals who understand both the tools and the design thinking needed to implement Agentic AI. This program helps you build a compelling e-Portfolio to showcase your skills to employers.

What skills are required to become an AI agent developer?

You need a mix of technical and strategic skills. This includes Prompt Engineering, RAG workflows, building multi-agent systems, integrating external tools with memory, and understanding responsible AI practices like risk management and governance.

What kind of AI agent jobs and AI agent career path options does this program prepare me for?

The demand for people who understand Agentic AI is growing a lot faster than the supply. This program sets you up for dedicated AI career paths, but it's equally valuable if you want to stay in your current field and become the go-to AI expert on your team. Because the course is so hands-on, you will also build a portfolio of projects to prove your skills in your next interview.

Other Queries

What is an AI agent, and how does it work?

Agentic AI refers to systems that can act autonomously, reason independently, and execute complex tasks with minimal human oversight. They work by combining Large Language Models (LLMs) with external tools, memory (short and long-term), and reasoning frameworks to solve dynamic business problems.

What is the architecture of an AI agent?

An AI agent's architecture involves an underlying foundational model (like an LLM) connected to external tools and a memory system. Advanced setups use multi-agent architectures, where multiple specialized AI agents interact and coordinate to solve complex problems collaboratively and at scale.

What are some real-world AI agent examples, and what are the primary use cases of AI agents in business?

Businesses use them to automate complex, multi-step workflows. Businesses use them to automate complex, multi-step workflows. Real-world applications covered in the program include solving common business challenges and optimizing processes across marketing, sales, and operations. These practical AI agent examples demonstrate how you can drive innovation and operational efficiency.

How does mastering AI give me a competitive edge in the job market?

Mastering AI gives you a competitive edge by equipping you with the exact skills organizations need as they rewire their operations to generate future value. With a large number of companies already integrating generative and analytical AI into their business functions, the ability to build intelligent solutions is highly sought after. As NVIDIA CEO Jensen Huang stated, “AI won’t take your job, the person who uses AI will take your job.” By learning to use AI effectively, you develop the most valuable skill needed this decade to stay relevant, contribute meaningfully, and capture value in your industry.

What is the best way to learn AI agents in 2026?

The best way to learn is through a structured, hands-on approach that matches your technical comfort level. This program offers a Flexible Learning Track where you can choose a coding-based track (Python-focused) or a no-code, tools-based track at the outset.

Got more questions? Talk to us

Connect with our advisors and get your queries resolved

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

Solve Business Problems with Agentic AI

Post Graduate Program in AI Agents for Business Applications

Delivered in collaboration with Great Learning

Learn more about the course

Post Graduate Program in AI Agents for Business Applications

Elevate Your Career with AI

Earn a certificate of completion from Texas McCombs

Why Choose This Program

Learn from renowned faculty and experts

Choose to learn with or without code

Hands-on learning

Learning support

Create a compelling e-portfolio

Earn recognized credentials

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

This Program Is Ideal for

Experience a Unique Learning Journey

Learn from world-renowned faculty

Engage with your mentors

Work on hands-on projects

Get personalized assistance

Unique learning journey

Weekly live sessions

Peer-to-Peer Learning

Industry-Relevant Curriculum

Get personalized assistance

On-Campus Immersion (Optional Paid Program)

Comprehensive Curriculum

PRE-WORK

Introduction to AI Landscape

Hands-On Tool Introduction and Setup

MODULE 01: AGENTIC AI FOUNDATIONS

Introduction to Generative AI and Large Language Models

Prompt Engineering and Retrieval Augmented Generation

Project Week

MODULE 02: BUSINESS APPLICATIONS WITH AGENTIC AI

Introduction to AI Agents

Incorporating Tools and Memory in Agents

Planning and Reasoning

Learning Break

Project Week

MODULE 03: ADVANCED AGENTIC AI SOLUTIONS

Multi-Agent Systems

Testing and Evaluation of Agentic Systems

Securing Agentic AI Solutions

Project Week

SELF-PACED COURSE

Multimodal Agentic AI (Masterclass only)

Work on Hands-On Projects and Case Studies

Company Financial Report Q&A Bot

Patient Support & Medical Info Agent

Intelligent Document Processing System for Legal Firm

Financial Research Analyst Agent

Travel Agent Application

Healthcare Startup Application

Automated Software Development Application

Quality Assurance for Customer Service Chatbot

Retail Order Query Chatbot

HR Policy Query Bot

Learn In-Demand AI Tools and Techniques

Earn a certificate of completion

Meet Your Faculty

Dr. Kumar Muthuraman