Emerging Business Applications of Machine Learning & Artificial Intelligences

Course details

This course is designed for PGDM and MBA students to understand the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML) from a management/business applications perspective. The course starts with essential math and statistics concepts and gradually progresses to cover key AI and ML topics. Students will learn mathematical and statistical principles, develop foundational Python and applied data science skills and understand the fundamentals of big data, machine learning and artificial intelligence. By the end of the course, students will have a solid foundation in AI and ML principles and how they apply to business contexts such as Marketing, Finance, HR etc.

Start Date

Spring 2024 Semester

Target Audience

2nd & 4th semester
MBA and PGDM students

Duration

Co-terminus with Spring Semester at ABBS

Key Features

Course taught by distinguished international faculty with combination of online asynchronous and online synchronous delivery of core content
Face to face weekly tutorial sessions by qualified teaching instructors trained in the course content by the international faculty
One interactive session per week with international faculty covering latest AI-ML industry trends, innovations and topics
Exposure to AI-ML applications across domains such as marketing, finance, & HR and learning from real-world business use cases and practical business challenges
Certification on successful completion of the course

Course Outcomes

Understand the meaning, purpose, scope, stages, business applications of AI and ML
Gain an in-depth understanding of data science processes
Understand the concepts of supervised and unsupervised learning, recommendation engines and time series modelling
Understand deep learning and its applications
Comprehend neural networks, and traverse the layers of data abstraction
Understand the fundamentals of natural language processing (NLP)
Learn how to apply machine learning and deep learning to NLP
Understand Artificial Intelligence and Machine Learning applications and be able to select appropriate algorithms and methods for various use cases and construct an efficient and successful AI strategy an AI project
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

Learning path

Unit 1 - Statistical Thinking and Data Visualization
Unit 2 - Supervised Learning
Unit 3 - Machine Learning & Unsupervised Learning
Unit 4 - AI Applications in Business

Topics covered

Business of AI
Introduction To Artificial Intelligence
Explosion In AI
Business Application and Its Limitations
Building AI Project & ROI Calculation
What Is Data?
Numerical And Textual Data
Graphs & Networks
Time Series Data
Different Types Of Data Objects
Understanding Visual Metrics: Mean, Median & Mode
Visualizing Data
Data Manipulation

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
Case Study
Introduction To Classification
Logistic Regression
Setting Up Threshold
Performance Measures - Precision & Recall
Evaluation Of Models
Case Study
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 Successful AI Product

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 KNIME
Ensemble Techniques
Introduction To Decision Trees
CART
Pruning
Ensemble Techniques
Random Forest
Case Study

Introduction To Clustering
Types Of Clustering
K-Means Clustering
Importance Of Scaling
Applications Of Clustering
Advantages & Disadvantages Of Clustering
Visual Analysis
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
Introduction To Recommendation Systems
Content Based Filtering
Collaborative Filtering
Similarity Measures
Case Study
Hybrid Systems

Introduction To Natural Language Processing (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
Case Study
Introduction To Computer Vision
Types Of CV Problems
Pixel
How Does The Computer See An Image?
3D Images
Resolution
Convolution & Pooling
Convolutional Neural Networks
Case Study

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 And Recalibration

Real-time project under guidance of teaching instructor, where you will learn to practically implement the no code approach for solving business problems. Study the market for opportunities and pitch a business plan for an AI-based product to convince employers and investors. You should put forth a market study (market size, competition & consumer), a product requirement document (data & people), the road map for implementation along with financials, business impact, etc.

Faculty Members

Prof. Varol Kayhan PhD.

University of South Florida (USF)

Dr Kayhan has been with USF since 2010 and teaches students... Read more

Prof. Dan Conway Ph.D.

University of Arkansas

Dr. Daniel Conway is Teaching Professor and Associate Director... Read more

Prof. Gaurav Jetley Ph.D.

Colorado State University

Dr Jetley's research interests are in the areas of health IT... Read more

Prof. Ran Zhang Ph.D.

Texas Tech University

Dr Zhang's research interests are in areas of Economics of... Read more