Post Graduate Program in Artificial Intelligence for Leaders

McCombs School of Business

in partnership with Great Learning

How long?

  • 19 weeks
  • online

What are the topics?

McCombs School of Business

in partnership with Great Learning


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Who should attend

AI for Leaders is an intensive online program for leaders who want to:

  • Understand enough AI to be able to make important choices and decisions
  • Develop the ability to identify scope and manage projects in AI
  • Deliver transformative projects to external and internal clients and stakeholders
  • Manage technical teams through the lifecycle of AI projects
  • Make appropriate choices when deciding between ‘tech stacks’ or products
  • Lead organizations new to the AI world as they develop AI-enabled products and services

About the course

Leverage the power of AI to become a qualified business leader and improve business outcomes

Our curriculum has been carefully-crafted to provide you with the breadth and depth you need to make smarter business decisions, lead AI teams, and devise an AI strategy for your organization. Accordingly, it covers the most business-relevant technologies and diverse industry applications to turn you into an AI-empowered leader.

Understanding AI through Data

Week 1 – Business of AI

  • Introduction to Artificial Intelligence
  • Explosion in AI
  • Business Applications and Limitations
  • Building an AI project
  • ROI Calculation
  • Case Study

Week 2 – Data Visualization using Azure ML

  • What is Data?
  • Numerical and Textual data
  • Graphs and Networks
  • Time Series Data
  • Different Types of Data Objects
  • Understanding Visual Metrics – Mean, Median & Mode
  • Introduction to Cloud Platforms – Azure ML
  • Visualizing Data using Azure ML Studio
  • Data Manipulation using Azure ML Studio

Supervised Machine Learning

Week 3 – Regression

  • Introduction to Regression
  • Linear Regression
  • Multivariate Linear Regression
  • Categorical Independent Variable in Regression
  • Root Mean Square Error and Mean Absolute Error
  • Linear Regression – Pros & Cons
  • Hands-on using Azure ML
  • Case Study Session with Experts

Week 4 – Classification

  • Introduction to Classification
  • Logistic Regression
  • Setting Up Threshold
  • Performance Measures – Precision & Recall
  • Naïve Bayes
  • Evaluation of Models
  • Hands-on using Azure ML
  • Case Study Session with Experts

Neural Networks & Ensemble Techniques

Week 5 – Neural Networks

  • Introduction to Neural Networks
  • Activation Function
  • Feed Forward Neural Network
  • Topology of a Neural Network
  • Error & Loss Function
  • Training a Neural Network
  • Optimizing a Neural Network
  • Hands-on using Azure ML

Week 6 – Ensemble Techniques

  • Introduction to Decision Trees
  • CART
  • Pruning
  • Ensemble Techniques
  • Random Forest
  • Hands-on using Azure ML

Unsupervised Machine Learning

Week 7 – Clustering & Dimensionality Reduction

  • Introduction to Clustering
  • Types of Clustering
  • K Means Clustering
  • Importance of Scaling
  • Applications of Clustering
  • Advantages and Disadvantages of Clustering
  • Visual Analysis
  • Hands-on using Azure ML

Week 8 – Recommendation Systems

  • Introduction to Recommendation Systems
  • Content-Based Filtering
  • Collaborative Filtering
  • Similarity Measures
  • Case Study
  • Hybrid Systems
  • Hands-on using Azure ML
  • Case Study Session with Experts

Week 9 - Break

Deep Learning – CV & NLP

Week 10 - Natural Language Processing (NLP)

  • Introduction to NLP
  • Different Tasks in NLP
  • How are NLP Problems Solved?
  • Text Extraction/ Web Scraping
  • Building a Model
  • Case Study – Sentiment Analysis
  • NLP Demonstration on Sentiment Analysis
  • Hands-on using AWS
  • Case Study Session with Experts

Week 11 – Computer Vision (CV)

  • Introduction to Computer Vision
  • Types of CV Problems
  • Pixel
  • How does a Computer See an Image?
  • 3D Images
  • Resolution
  • Convolution & Pooling
  • Convolutional Neural Networks
  • Hands on Using AWS
  • Case Study Session with Experts

AI in Practice

Week 12 – Jumpstarting AI

  • Transfer Learning
  • How it Works
  • Applications of Transfer Learning – Advantages vs. Disadvantages
  • Dealing with Imbalanced Data - Data Augmentation
  • Data Augmentation Types
  • Model Deployment
  • Modes of Training
  • Serialization
  • Model Monitoring & Recalibration

Week 13 – Building POC for AI Projects

  • Building POC – Outline
  • Solution at a Glance
  • Market Potential
  • Threats & Opportunities
  • Requirements – Data & People
  • Product Development Roadmap
  • Expansion Plan
  • AI Techniques & their Relevance to Domains
  • Identifying AI Use Cases
  • Tips for Building a Successful AI Product

Week 14 – Building AI Teams & Driving Data Culture

  • Service vs Product Companies
  • AI Team Composition
  • Centralized vs Distributed AI Teams
  • How to Keep your Team Motivated
  • Handling Resistance from Senior Management
  • Coaching Others
  • Managing Portfolio of Projects
  • Scaling AI Teams

Capstone Project Certificate from The University of Texas at Austin

Program Benefits

  • Mentored Learning sessions with Industry Experts
  • Real-world case studies to build industry context
  • Projects that don’t require coding experience
  • Domain understanding coupled with technical coverage
  • Certificate from The Universityof Texas at Austin
  • Capstone Project to consolidate your learning


Kumar Muthuraman

Biography Kumar Muthuraman is the H. Timothy (Tim) Harkins Centennial Professor in the Department of Information, Risk and Operations Management and the Department of Finance. He received his Ph.D. from Stanford University. Dr. Muthuraman’s research focuses on decision making under uncertainty. A...

Abhinanda Sarkar

Dr. Abhinanda Sarkar is the Academic Director at Great Learning for Data Science and Machine Learning Programs. Dr. Sarkar received his B.Stat. and M.Stat. degrees from the Indian Statistical Institute (ISI) and a Ph.D. in Statistics from Stanford University. He has taught applied mathematics at ...

Thadikamala Shyla Kumar

Senior IT professional with 18+ years of domestic and international experience, in handling large IT Transformation programs / projects / people primarily in the Banking and IT Service industry space. Senior executive responsible for driving strategic initiatives, managing multi-million dollar ...

Itti Singh

Itti comes with a rich experience of 12+ years in driving significant business results and process improvements employing the power of analytics & ML. She has built and led growth-oriented analytics and insights teams for Banking & Financial Services and Retail conglomerates like HSBC, Ci...

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Post Graduate Program in Artificial Intelligence for Leaders at McCombs School of Business

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