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Course Content
Syllabus
Course Objective: 1. Equip students with foundational knowledge in AI & ML, including understanding technology landscape, tools/platforms for deployment, data importance, statistical foundations, and data visualization for effective decision-making. 2. Essential concepts in machine learning, including supervised and unsupervised learning, ensemble techniques, recommendation systems, reinforcement learning, and their applications. 3. Equip students with a comprehensive understanding of key machine learning algorithms and techniques, including linear regression, logistic regression, decision trees, random forests, KNN, neural networks, deep learning, visualization, NLP, and text analytics. 4. Prepare students to lead digital transformation initiatives by developing AI & ML strategies aligned with organizational goals, ensuring business model fit, ROI, success measures, and addressing data requirements. 5. Equip management students with essential visualization techniques, emphasizing context, storytelling, and utilizing data to influence decision-making effectively.
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UNIT-I TECHNOLOGY OVERVIEW AND FUNDAMENTALS
UNIT-II UNBOXING ML AND ITS APPLICATIONS
UNIT-III UNBOXING AI AND ITS APPLICATIONS
UNIT-IV AI & ML FOR BUSINESS EXCELLENCE
UNIT-V FRAMEWORKS FOR DELIVERING AI SOLUTIONS
TEXT BOOKS & REFERENCE BOOKS
LECTURE NOTES
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Question Bank
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Puzzles
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23BAT615 & Artificial Intelligence for Managers
  1. Artificial Intelligence for Managers: Leverage the Power of AI to Transform Organizations & Reshape Your Career (English Edition) by “Malay a Upadhyay”, 1st edition2021
  2. Artificial Intelligence for Managers:  For Individuals Aspiring to Get into the AI Domain by “RakeshDandu”, 1st edition 2020.
  3.  HBR Guide to AI Basics for Managers by “Harvard Business School “, 1st edition, 2023.
  4. Artificial Intelligence: A Modern Approach | Fourth Edition| By Pearson Fourth Edition, Kindle Edition by “Norvig Russell “.
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