Introduction to AI/ML Part 1
· AI: When it started and how it evolved?
· Tools, technologies and techniques that model intelligence and are part of AI right from classical AI to modern generative AI.
· Modelling and Solving problem using AI. What can be done using AI?
· Machine Learning, Deep Machine Learning, Generative AI, Natural Language Processing, etc.
· What is missing in current AI and issues with AI?
Introduction to AI/ML Part 2
· Using effective combination of classical and modern AI: integrating data driven intelligence v/s knowledge (cognitive) driven intelligence
· How organizations using effective ACID (AI/Analytics, Cloud, IOT and Data) to enhance customer experiences, optimize operations and offer new business models?
· Using power of Generative AI
Intelligence everywhere, Role of AI in Hyper-personalization
· Role of AI in hyper personalization
· Understanding filtering techniques: collaborative filtering, content filtering, demographics and knowledge-based filtering and their roles in P&R (personalization and recommendation)
· Modelling N=1 (segment of 1), real time and contextual intelligence such as customer intelligence
· Integrating intelligence everywhere: in touch-points, channels, UIs, work-flows and processes.
Solving real-world problems using AI
· Case studies on AI.
· Interaction with participants, understanding their problems and discussing solutions.