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Artificial Intelligence PPT Presentation.pptx
- 1. Artificial Intelligence Course CourseFacilitator Prashant Kumar AI Architect & Digital Transformation Leader
- 2. What is AI AI(Artificial Intelligence) is the ability of machines to perform tasks that typically require human intelligence. Phases of AI • Machine Learning (ML) – Pattern Learning • Deep Learning (DL) – Representation Learning • Generative AI (GenAI) – Content Creation • Agentic AI – Autonomous Action & Tool Use Why AI Matters • Automates repetitive, rule-based, and high-volume tasks. • Enhances human capabilities with faster insights and improved accuracy. • Accelerates innovation in every industry—software, business operations, healthcare, finance, retail, and more. • Enables new experiences such as conversational assistants, personalized recommendations, and intelligent automation. Use Cases • Healthcare: Diagnosis support, medical imaging • Finance: Credit scoring, risk modeling, fraud analytics • Retail: Inventory optimization, dynamic pricing • Manufacturing: Quality inspection, robotics • Marketing: Targeted campaigns, customer segmentation Artificial Intelligence Course
- 3. Session 1 -Intro to AI & ML • What is AI, ML, DL • Learning types • Data, features, labels • Activity: map problems to ML Session 5 – Deep Learning concepts • What is Deep Learning? • Key Component • How Deep Learning Works • Common Deep Learning Architectures • Deep Learning Applications Artificial Intelligence Course Session 2 - Core ML Concepts • Bias/variance • Over/underfitting • Feature engineering • Metrics • Confusion matrix Session 3 - ML Algorithms • Regression • Decision trees • Random forests • Gradient boosting • Neural nets intro Session 4 - AI/ML Use Cases • Industry case studies • Everyday Applications • Business & Enterprise • Product & User Experience
- 4. Session 6 -Deep Learning Architectures & Applications • Convolutional Neural Networks (CNNs) • Recurrent Neural Networks (RNNs) • Transformers (Modern DL) • Autoencoders & Representation Learning • Generative Deep Learning Session 10 – Agentic AI concepts • What is Agentic AI? • AI Agents, Single & Multi Agent Systems • Agentic AI frameworks • MCP and MCP Server Artificial Intelligence Course Session 7 - Generative AI Fundamentals • GenAI vs discriminative • LLMs • Prompting, fine-tuning • Prompt Engineering Session 8 - GenAI by Modality • Text, image, audio, video models • Different models and their comparison Session 9 – Gen AI advance concepts • RAG • Embeddings • Vector search • Vector DBs (Pinecone, Chroma)
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