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AI for Business Innovation: From GenAI to POCs

AI for Business Innovation: From GenAI to POCs

10.09 hrs 1 project

AI for Business provides learners with a robust understanding of AI, Generative AI, Machine Learning, Natural Language Processing and Computer Vision. By utilizing KNIME workflows and engaging in proof-of-concept development

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Course outline

Industry focussed curriculum designed by experts

Introduction to AI

4 Videos

In this module, you will delve into the fundamentals of AI, essential terminology and its practical significance. Case studies and discussions will illustrate the application of AI across various industries, thereby establishing a robust foundation for advanced learning.

4 items

0.54 hr

  • Overview of AI
  • Deep Learning Terminologies
  • Machine Learning Terminologies
  • Case Study

Fundamentals of Generative AI

7 Videos

This module addresses the basics of Generative AI, its historical context and how it differs from traditional AI. You will also investigate its impact on industries and discover how generative models effectively address real-world business challenges.

7 items

1.09 hr

  • Introduction to Generative AI - Definitions
  • Introduction to Generative AI - Mind Map
  • Supervised and Unsupervised Learning
  • Discriminative AI vs. Generative AI
  • Brief History of Generative AI
  • A Peek into Generative AI Models
  • Business Problems Solved by Generative AI

Core Pillars of AI: ML, Neural Networks, NLP, and Computer Vision

14 Videos

In this module, you will examine the core pillars of AI, which include Machine Learning, Neural Networks, Natural Language Processing and Computer Vision. The course integrates both theory and practice to enhance your technical knowledge for the effective application of these technologies.

14 items

1.58 hr

  • Introduction to Machine Learning and its Types
  • Introduction to Neural Networks
  • Feedforward Neural Network
  • Topology of a Neural Network
  • Error and Loss Function
  • What is NLP
  • Common NLP Terminology
  • Applications of NLP
  • Challenges in NLP
  • Introduction to Computer Vision
  • Types of Computer Vision Problems
  • Pixel
  • How a Computer Sees an Image
  • Convolution

KNIME for AI Practitioners: A Practical Guide

10 Videos

This module presents KNIME, an open-source platform designed for analytics and Machine Learning. You will acquire skills in installation, features, visualization, and practical workflows, equipping you with hands-on experience for developing real-world AI projects.

10 items

3.16 hr

  • The AI, Data Science and Machine Learning Platforms
  • KNIME - Overview of Features
  • KNIME - What and Why
  • KNIME - Installation and Demo
  • KNIME - Visualization Part 1
  • KNIME - Visualization Part 2
  • KNIME - Regression Hands-on
  • KNIME - Logistic Regression Hands-on
  • KNIME - KMeans Hands-on
  • KNIME - Neural Network Regression

Building a Proof of Concept for AI Projects

15 Videos

In this section, you will learn how to design, validate, and present AI proof-of-concepts. The topics covered will include business alignment, market research, technical requirements, roadmaps and strategies for scaling to ensure the successful execution of AI projects.

15 items

2.49 hr

  • Building POC Outline
  • Company Values
  • Solution at a glance
  • Market Potential
  • Threats and Opportunities as the Market Grows
  • Target Customers
  • Requirements, Data, and People
  • Product Roadmap
  • Expansion Plan
  • Business Plan Financially
  • Different AI Techniques in Industry with Examples
  • AI Techniques & Their Relevance to Domains
  • Identifying AI Use Cases
  • Narrowing in on AI Use Case
  • Tips for Building a Successful AI Product

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Guided Projects

Solve real-world projects with a step-by-step guide, starter code templates, and access to model solutions to boost your skills and build a standout resume.

  • GUIDED PROJECT 1
  • Customer Segmentation for E-commerce using KNIME
  • This project focuses on implementing customer segmentation for an e-commerce platform using the KNIME Analytics Platform. By analyzing customer transaction data, learners can identify distinct customer segments, enabling businesses to tailor their marketing strategies more efficiently. The project reinforces fundamental concepts of AI and practical skills in data analysis, utilizing generative AI techniques relevant to e-commerce. This hands-on experience will empower learners to apply AI concepts in real-world business settings.
Foundations of AI ML and Deep Learning
Generative AI principles & business use cases
Core AI pillars
Practical AI workflow with KNIME
Building & presenting AI Proof of Concept

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Course Instructors

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Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning

Dr. Abhinanda Sarkar has B.Stat. and M.Stat. degrees from the Indian Statistical Institute (ISI) and a Ph.D. in Statistics from Stanford University. He was a lecturer at Massachusetts Institute of Technology (MIT) and a research staff member at IBM. Post this he spent a decade at General Electric (GE). He has provided committee service for the University Grants Commission (UGC) of the Government of India, for infoDev – a World Bank program, and for the National Association of Software and Services Companies (NASSCOM). He is a recipient of the ISI Alumni Association Medal, an IBM Invention Achievement Award, and the Radhakrishan Mentor Award from GE India. He is a seasoned academician and has taught at Stanford, ISI Delhi, the Indian Institute of Management (IIM-Bangalore), and the Indian Institute of Science. Currently, he is a Full-Time Faculty at Great Lakes. He is Associate Dean at the MYRA School of Business where he teaches courses such as business analytics, data mining, marketing research, and risk management. He is also co-founder of OmiX Labs – a startup company dedicated to low-cost medical diagnostics and nucleic acid testing.
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Dr. Pavankumar Gurazada

Senior Faculty, Academics, Great Learning

Dr. Pavankumar Gurazada brings a unique blend of industry experience and academic expertise, specializing in marketing, digital marketing, and machine learning. He is also a Data Science advisor and board member of Constems AI, a deep tech startup focused on building computer vision systems for Industry 4.0. Dr. Gurazada completed his Ph.D. from IIM Lucknow, with a research focus on using machine learning techniques to understand consumer engagement on social media. His research has been presented at prominent international conferences such as the EMAC Conference 2018, the China Internet+ Innovation and Entrepreneurship Conference 2019, and the NASMEI and MRSI conferences. His book, Marketing Analytics, published by Oxford University Press in March 2021, is a testament to his expertise in the field. He holds an MBA from IIM Bangalore and an Integrated Master’s degree in Science from IIT Bombay. With a career that spans roles in retail and B2B sales management, Dr. Gurazada’s industry experience includes leadership positions at Alghanim Retail in Kuwait and Saint Gobain in UAE & Oman, where he significantly contributed to business growth and managed distribution networks.

AI for Business Innovation: From GenAI to POCs

10.09 hrs 1 project

AI for Business Innovation: From GenAI to POCs

10.09 hrs 1 project
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