AI for Business - I

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Publisher: Prime Publishing House
ISBN: 9788199121331
Year: 2025
Pages: 122

AI for Business – I is a comprehensive and accessible introduction to the fundamentals of Artificial Intelligence and its transformative role in the modern business landscape. Designed for learners from diverse academic backgrounds, this book presents complex concepts in a simple, structured, and application-oriented manner.

The book covers essential topics such as the basics of Artificial Intelligence, key principles of Machine Learning, and the growing influence of AI across business functions including marketing, finance, human resources, operations, and customer service. It also explores real-world applications like chatbots, recommendation systems, and emerging technologies such as generative AI.

With a focus on practical understanding, real-life examples, and current trends, this book helps readers develop both conceptual clarity and awareness of how AI is reshaping industries. It also addresses important ethical considerations and highlights future career opportunities in the field.

An ideal resource for beginners, this book serves as a valuable guide for understanding and applying Artificial Intelligence in business contexts.

1. Introduction to Artificial Intelligence
1.1 Definition and History of AI
1.2 Types of AI: Narrow, General, and Super AI
1.3 Branches of AI: NLP, Computer Vision, Robotics Readings:
1.4 Real-world examples of AI in Business (Chatbots, Recommendation Engines)
1.5 Introduction to Generative AI (ChatGPT, Bard, Copilot) use cases and AI Integration in Modern Enterprises

2. Basics of Machine Learning
2.1 What is Machine Learning? – Definition and Categories
2.2 Supervised vs. Unsupervised Learning (with simple examples)
2.3 Role of data in ML: Training Data and Model Prediction
2.4 Applications of ML in Business: Credit Scoring, Customer Segmentation
2.5 Introduction to common ML tools (Google AutoML, Teachable Machine)

3. AI Applications in Business Functions
3.1 AI in Marketing: Customer Profiling, Personalized Ads
3.2 AI in Finance: Fraud Detection, Robo-Advisors
3.3 AI in HR: Resume Screening, Chatbots for Recruitment
3.4 Ethical Considerations in AI (Bias, Transparency, Job Displacement)
3.5 Future Trends and Career Paths in AI & ML

This textbook is aligned with the revised syllabus as outlined by the National Education Policy (NEP 2020) Open Electives (OE) Second Year BA / BSc / BCA / BBA (Semester - III)

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