Subject Details
Dept     : MBA
Sem      : 4
Regul    : 2019
Faculty : Ms. S. Pavithra Vanshi
phone  : NIL
E-mail  : cemba40
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Syllabus

UNIT
1
MACHINES AND AI

Introduction – Different types of Machines Learning and AI – Working Nature – AI Impact and Drive Business Model - 7 Rules of AI First Leadership

UNIT
2
DATA FOR AI

Data for AI - Importance of Alternative Data - Finding, Generating, and Managing Data - Integrating Data into Products - Steps to a Data Strategy

UNIT
3
CONVOLUTION NEURAL NETWORKS

Image classification - Text classification - Image classification and hyper-parameter tuning - Emerging NN architectures

UNIT
4
ISSUES, CONCERNS AND ETHICAL CONSIDERATIONS

Issues and Concern around AI – AI and Ethical Concerns – AI and Bias – AI: Ethics, Bias and Trust - Principles of ethical AI.

UNIT
5
AI AND SOCIETY

A realistic view of AI – Discrimination – Adversarial attacks on AI – AI and Developing economies – AI and Jobs

Reference Book:

1. Russel, “Artificial Intelligence 3e: A Modern Approach”, 3rd Edition, Pearson Education India, 2015. (Units - I, II, III, IV & V) 2. Artificial Intelligence 3e: A Modern Approach, “Artificial Intelligence For Dummies”, Wiley Publishers, 2018. 3 G Venkatesh and MadhavanMukund, “Computational Thinking: A Primer for Programmers and Data Scientists”, 1st Edition, Notion Press, 2021 4 Paul Deitel and Harvey Deitel, “Python for Programmers”, Pearson Education, 1st Edition, 2021

Text Book:

Joshi.P, “Artificial Intelligence: Building Intelligent Systems”, Prentice Hall India, 1st Edition, 2015. (Units - I, II, III, IV & V)

 

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