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AI For Business is simple version For S.Y.B.C.A(NEP 2020) 214F: AI for Business – I "AI for Business" would introduce Artificial Intelligence as a transformative technology with the potential to...

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AI for business
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AI For Business is simple version For S.Y.B.C.A(NEP 2020) 214F: AI for Business – I "AI for Business" would introduce Artificial Intelligence as a transformative technology with the potential to significantly impact businesses by enhancing efficiency, improving customer experiences, and driving innovation. It would outline that AI uses machine learning and data analysis to automate tasks and provide insights, offering benefits like deeper customer understanding and competitive advantage. The preface would also acknowledge the challenges and ethical considerations of AI adoption and the importance of preparing the workforce to leverage these new tools for sustainable growth.
The Role of AI in Modern Business: AI is fundamentally changing how businesses operate by integrating advanced technologies such as machine learning, natural language processing, and computer vision into daily operations. These technologies allow businesses to:
• Enhance Operational Efficiency: Automate routine tasks, reduce operational costs, and increase productivity by enabling faster and more accurate processes.
• Improve Decision-Making: Use predictive analytics to forecast trends, optimize supply chains, and make data-driven decisions that align with business goals.
• Personalize Customer Experiences: Leverage AI to analyze customer data and behavior, enabling personalized marketing, recommendations, and customer support.

1. Introduction to Artificial Intelligence........................................7
• Definition and history of AI
• Types of AI: Narrow,
• General, and Super AI
• Branches of AI: NLP, Computer vision, robotics
• Real-world examples of AI in business (chatbots, recommendation engines)
• Introduction to Generative AI (ChatGPT, Bard, Copilot)
2. Basics of Machine Learning.........................................44
• What is Machine Learning? – Definition and categories
• Supervised vs. Unsupervised learning (with simple examples)
• Role of data in ML: training data and model prediction
• Applications of ML in business: credit scoring, customer segmentation
• Introduction to common ML tools (Google AutoML, Teachable Machine)
3. AI Applications in Business Functions................82
• AI in marketing: customer profiling, personalized ads
• AI in finance: fraud detection, robo-advisors
• AI in HR: resume screening, chatbots for recruitment
• Ethical considerations in AI (bias, transparency, job displacement)
• Future trends and career paths in AI & ML

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