Solve Business Problems with Agentic AI

Post Graduate Program in AI Agents for Business Applications

Application closes on 14th May 2026

Delivered in collaboration with Great Learning

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Post Graduate Program in AI Agents for Business Applications

Application closes 14th May 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 out 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

Easy payment plans

Avail our EMI options & get financial assistance

INSTALLMENT PLANS

Upto 3 months Installment plans

Explore our flexible payment plans

View Plans

Third Party Credit Facilitators

Check out different payment options with third party credit facility providers

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

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: 14th May 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

Eligibility and Admissions

Fee and Payment

Other Queries

Program Details

What are the highlights of the Post Graduate Program in AI Agents for Business Applications?

The Postgraduate Program in AI Agents for Business Applications is a 12-week online program designed for knowledge professionals and business and technology experts looking to develop an industry-ready skill set in Agentic AI. Here are some of the program highlights: Program format: Delivered online through recorded lectures by Texas McCombs faculty and live masterclasses by industry experts by Texas McCombs faculty, interactive mentorship sessions, and recorded video lectures. Faculty and Mentors: Learn from world-renowned Texas McCombs faculty and global industry experts through recorded lectures and weekly live mentorship sessions. Flexible Learning Track: This program offers learners the flexibility to choose between two distinct tracks: a coding-based track (Python-focused) and a no-code, tools-based track. Learners select their preferred track at the outset of the program and complete all hands-on components using the tools and technologies aligned with their chosen track. Hands-on Learning: Apply knowledge to build intelligent AI systems through real-world projects and case studies. Peer Interaction: Gain peer networking opportunities with a global cohort of participants. Learning Support: Receive personalized assistance from a dedicated Program Manager and academic support through the Great Learning Community, Project Discussion Forums, and Peer Groups. Success Coach: Each participant will be assigned a Program Manager or Success Coach who will ensure the learning journey is in line with their career goals. Create a Compelling e-Portfolio: Build a portfolio to showcase your proficiency in AI tools and skills. Earn Recognized Credentials: Upon completion, earn a globally recognized Certificate of Completion from the McCombs School of Business at The University of Texas at Austin and also 2.5 Continuing Education Units (CEUs).

What are the learning outcomes of the online AI Agents course from the McCombs School of Business at The University of Texas at Austin?

By the end of this program, 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, and Retrieval-Augmented Generation to enhance business productivity. • Develop intelligent, context-aware single-agent systems by integrating tools and memory to automate workflows and improve operational efficiency. • Implement planning and reasoning strategies that enable autonomous agents to decompose tasks, adapt to dynamic scenarios, and solve complex business problems with AI-powered intelligent processes.

How will my performance be evaluated in this program?

Your performance in the Postgraduate Program in AI Agents for Business Applications will be evaluated through regular assessments, including projects and quizzes. These evaluations are designed to assess your understanding and application of key concepts, ensuring that you gain practical, hands-on experience in building AI systems.

What is the duration of this AI Agents course?

The duration of the Postgraduate Program in AI Agents for Business Applications is 12 weeks.

What is the required weekly time commitment?

The required weekly time commitment for the AI Agents for Business Applications program is 8 to 10 hours per week. This includes: • Structured learning modules with recorded video content • 8+ live interactive sessions (2 hours each) with industry practitioners

What career opportunities will I get after completing this AI Agents program?

Completing this PGP in AI Agents for Business Applications equips you with the skills to pursue roles where you can develop and manage intelligent AI systems across various industries. Depending on your background and experience, you may explore opportunities such as • AI Engineer • AI Consultant • AI Product Manager • Machine Learning Engineer • Agentic AI Developer/Engineer • Robotics and Autonomous Systems Engineer • AI Ethics and Governance Specialist

What role does Great Learning play in this AI Agents course?

Great Learning plays a pivotal role in the Postgraduate Program in AI Agents for Business Applications by providing comprehensive support and services to enhance your learning experience. These include: • Personalized Mentorship: Receive guidance from industry experts and mentors throughout the course. • E-Portfolio for Projects: Build a professional portfolio to showcase your skills to potential employers. • Learning support: Each participant will be assigned a Program Manager who will ensure the learning journey is in line with the participant's career goals. • AI-Assisted Learning: AI-powered tools support video content, project work, and practice activities to enhance your learning efficiency and engagement.

Is it an AI Agents course with a certificate?

Yes, upon successful completion of the Postgraduate Program in AI Agents for Business Applications, you will receive a Certificate of Completion from The McCombs School of Business at The University of Texas at Austin, recognizing your expertise in Agentic AI and its business applications.

Who are the industry mentors providing guidance throughout the program?

The industry mentors for the Postgraduate Program in AI Agents for Business Applications include experienced professionals from leading companies, offering real-world insights and guidance throughout the program. These mentors come from diverse backgrounds, ensuring that you gain practical knowledge and expertise from various sectors. Below are the details of the mentors: Mentor Name Position Organization Kalle Bylin Data Engineer Workday Bhaskarjit Sarmah Head RQA AI Labs BlackRock Tanya Glozman Applied Science - AI/ML Apple Bridget Huang Tech Lead, Engineering Capital One Vinicio De Sola Senior AI Engineer Newmark

Who are the faculty members teaching this AI Agents course?

The Postgraduate Program in AI Agents for Business Applications is taught by world-class faculty with years of collective experience in academia and industry. These faculty members bring a blend of theoretical knowledge and practical insights, ensuring a comprehensive learning experience. Dr. Kumar Muthuraman Faculty Director, Center for Analytics and Transformative Technologies, McCombs School of Business, UT Austin. Dr. Daniel A. Mitchell Clinical Assistant Professor, Department of Information, Risk & Operations Management, McCombs School of Business, UT Austin.

What projects are included in the AI Agents certificate program?

The program includes 3 hands-on projects and 15+ real-world case studies spanning industries like Finance, Healthcare, Legal, Retail, and HR. Here are sample projects that the Postgraduate Program in AI Agents for Business Applications includes: Project Title: Company Financial Report Q&A Bot Objective: Extract key information from financial documents using RAG for better decision-making Domain: BFSI, Financial Document Analysis Skills: Generative AI, Large Language Models, Prompt Engineering, Hugging Face, RAG, Vector Databases Project Title: Patient Support & Medical Info Agent Objective: Develop a healthcare assistant for understanding health records and sourcing medical information Domain: Healthcare Skills: Agentic AI, Large Language Models, Prompt Engineering, Hugging Face, LangChain, LangGraph, MCP Project Title: Intelligent Document Processing System for Legal Firm Objective: Automate the processing and management of legal documents to enhance workflow efficiency. Domain: Legal Document Processing Skills: Agentic AI, Large Language Models, Multi-Agent Systems, Workflow Automation, LangGraph, LangSmith, Human Feedback Loops, Legal Document Compliance

Which languages and tools will I learn in this AI Agents course online?

In the Postgraduate Program in AI Agents for Business Applications, you will learn to work with 20+ in-demand tools, including: - Python - LangChain - LangGraph - MCP Framework - LangSmith - LangChain ReAct - OpenAI APIs - ChatGPT - Hugging Face - ChromaDB - Google Colab - Streamlit - Transformers - Pandas - FAISS - Llama Cpp - Gemini - External APIs - Claude - n8n - DynaBench - NotebookLM These tools are essential for building and deploying advanced AI agents, offering you practical experience with widely used technologies in the field.

What is the curriculum of this AI Agents course?

The Postgraduate Program in AI Agents for Business Applications covers the following key modules: Pre-Work: Introduction to the AI Landscape and hands-on tool setup tailored to your chosen path (Code or No-Code tools). Module 1: Foundations of Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). Module 2: Developing AI agents, incorporating tools and memory, and applying planning and reasoning strategies. Module 3: Multi-agent systems, testing, evaluation, and securing agentic AI solutions. Self-Paced Modules: Claude-Based AI Workflows (allowing you to design real-world AI workflows using the Claude ecosystem via either a No-Code or Code track) and a Masterclass on Multimodal Agentic AI (focusing on cross-modal reasoning, attention, and alignment across text, vision, and other modalities). The program includes hands-on projects and case studies, ensuring practical learning in AI agent development and deployment.

What is the ranking of the University of Texas at Austin (UT Austin)?

UT Austin is recognized as a top-tier institution. According to the QS World University Rankings 2026, it lands at #1 in Texas, #20 in the U.S., and #68 globally. According to U.S. News & World Report’s Best Colleges 2026, the university ranks #30 nationally and #7 Public University in the U.S. (as per U.S. News & World Report's Best Colleges 2026).

Will I receive alumni status?

No, learners who complete the PGP in AI Agents for Business Applications from the McCombs School of Business at The University of Texas at Austin do not receive alumni status.

Can I pursue this course while working full-time?

Yes, you can pursue this AI Agents for Business Applications program while working full-time. The program is designed for working professionals, with a weekly time commitment of 8 to 10 hours. It includes structured learning modules, recorded video content, and live sessions on weekends, allowing you to manage your learning alongside your professional responsibilities. The flexible format ensures you can balance both work and study effectively.

Eligibility and Admissions

Who is the AI Agents program ideal for?

This AI Agents program is ideal 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 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.

Do I need to know how to code to take this program?

No, coding experience is not strictly required. The program offers a Flexible Learning Track that allows you to choose between two distinct paths at the outset of the program: a coding-based track (Python-focused) and a no-code, tools-based track. You will complete all hands-on components using the specific tools aligned with your chosen path.

What is the admission process for this program?

The admission process is conducted on a rolling basis and will close once the requisite number of candidates has been enrolled. APPLY Fill out an online application form REVIEW Eligible applications will be reviewed by a panel from Great Learning JOIN THE PROGRAM An offer letter will be sent to the selected candidates

Will this program help me if I am looking to transition into AI from a non-technical background?

Yes. The no-code track is specifically designed for professionals without a programming background. You will work with tools like Claude, n8n, and NotebookLM to build real AI workflows without writing code. Many business, operations, and consulting professionals use this path to transition into AI-adjacent roles such as AI Product Manager or AI Consultant.

Fee and Payment

What is the AI Agents course fee?

The total program fee is USD 3450. Please contact the Program Advisor from Great Learning for more information on offers, payment plans, and eligibility for financial assistance.

Other Queries

What is an AI Agent?

An AI agent is an autonomous system that can perceive its environment, make decisions, and take actions to achieve specific goals. It uses AI technologies like machine learning and reasoning to perform tasks with minimal human intervention.

What is the difference between an Agentic AI course and an AI Agents course?

The difference between an Agentic AI course and an AI Agents course lies in their focus areas: Agentic AI Course: Focuses on building AI systems that autonomously make decisions, reason, and operate independently, with an emphasis on the theory and design of such systems. AI Agents Course: Concentrates on the practical aspects of designing, developing, and deploying AI agents that perform specific tasks autonomously, using various tools and frameworks. In short, Agentic AI is more about the theory of autonomous decision-making, while AI Agents focuses on creating and applying these agents in real-world scenarios.

How strong is the job market for AI Agents professionals right now?

The demand for AI professionals is growing at an exceptional pace. According to a PwC 2025 survey, 79% of companies have already adopted AI agents, and organizations are rapidly moving from experimentation to real-world deployment. This has created an acute shortage of professionals who can design, build, and manage agentic AI systems, making this one of the most sought-after skill sets in the market today.

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

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Installment 1	1000 USD
Installment 2	1450 USD

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

Upskill Your Teams with Future-Ready Skills

Enter your organisation name

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