This is a cutting-edge business application oriented program for AI technologists, specialists and enthusiasts to expedite their AI implementation skills in the industry. Over a period of 9 months, participants gain a rigorous understanding of all possible machine learning and deep learning algorithms in the context of solving current and future real world business problems using AI.

The programme provides an overview of various:

Rigorous understanding of various machine learning algorithms (supervised and unsupervised learning) and deep learning algorithms (text, speech, image)
Foundational AI business applications (sentiment analysis, recommender systems, chatbots, audio and image processing)
Foundation of Gen AI, Implementation of GenAI applications on Cloud AI Models
AI change and project management techniques and tools (Agile, Scrum)
Industry specific AI use cases (Fintech and Supply chain)
Industry best practices in AI transformation (regulations, ethics and cyber risk)

Program Outcomes

Understand and appreciate the depth of AI's impact - emerging business models, disrupted business functions, predictive analytics methodologies, digital economy canvas.
Identify the most suitable machine learning or deep learning algorithms to solve specific business challenges, covering text, speech, and video.
Learn the inner workings of widely used machine learning and deep learning algorithms - from data to insights generation, and their interpretation.
Gain understanding of the foundational business applications using AI & ML such as sentiment analysis, recommender systems, chatbots, audio and image processing.
Acquire hands-on experience through project demos in real-world AI applications like heart disease prediction, product pricing, climate change analysis, etc.
Build Gen AI applications, chatbots, and bot frameworks on Cloud AI Models
Learn from successful AI implementation use cases in Fintech and Supply Chain, and apply them to your industry.
Adhere to industry practices regarding regulations, AI ethics, and cyber risk when deploying machine learning or deep learning algorithms.
Apply Agile Methodologies, Scrum project management, and change management principles for successful AI program delivery.
Develop strategies for AI product adoption, and effective management of AI transformation.

Desired Candidate Profile

Eligibility Criteria:

To be eligible, applicants must have a Bachelor's or Master's degree in Management, Computer
Science, Engineering, Mathematics, Statistics, Economics, or Science with a minimum of 50%
marks earned during graduation and 2 years of post-qualification experience.

Course Modules

Program Curriculum

AI/ML an Imperative for Digital Businesses

Module 1:

The AI & ML landscape - Emerging Business Models
Predictive Analytics Methodology
Impact of AI technologies - Digital Economy Canvas
Data Preparation for AI/ML - Imputation Methods

Fundamentals of Supervised Machine Learning

Module 2:

Predictive Modelling using regression - Business scenarios / Best practices
Building explainable models using CART (Non-Parametric)
Predicting customer behavior (classification models) with less data
Advance predictive models by using big data (Non-Parametric)

Understanding Unsupervised Machine Learning

Module 3:

Customer behavior analysis using segmentation
Market Basket Analysis
Statistical methods to create implicit scoring factors (FA and PCA)

Introduction to Deep Learning Algorithms

Module 4:

A walkthrough with neural networks and Deep Learning
Advance techniques to get forecast of business KPIs (estimate of sales and demand)
Science behind AI for speech processing
How AI companies process text data
Understanding how vision works

Practicing Machine Learning

Module 5: