AI for You: Hands-On Designing Intelligent and Personalized Systems (Part1)

Imagine scrolling through your favorite social media platform, discovering a perfectly curated news feed, or finding the ideal product on an e-commerce site, all tailored just for you. AI for You brings this magic of personalization to life, showing how artificial intelligence powers recommender systems to enhance everyday experiences across diverse domains like art, healthcare, entertainment, and shopping. 

This beginner-friendly course uses relatable examples, hands-on activities, and a case study approach to introduce the fundamentals of recommender systems and the AI algorithms behind them. No coding or AI background is needed—pre-built tools and guided exercises make learning accessible and fun. Participants will progress from traditional methods to cuttingedge generative AI, exploring real-world applications like personalized art curation or health recommendations. With a focus on human-centered design and ethics, the course equips you to create intelligent, personalized systems. Delivered over an intensive week with morning theory sessions and afternoon hands-on activities, it includes group projects, interactive demos, and immersive art therapy prizes for top teams, ensuring engagement for all.

This course will cover:

• Introduction to personalization and recommender systems (with everyday examples like social media feeds and e-commerce suggestions)
• Core methods: collaborative filtering, content-based filtering, and hybrid approaches
• Computational techniques for designing recommender systems
• Generative AI for creative and personalized suggestions
• Reinforcement learning for adaptive recommendations
• Human-centered recommendation systems (fair, ethical, and user-first design)
• Evaluating recommender systems (offline tests, user studies, real-world metrics)
• LangChain and agentic AI for interactive, conversational recommendations

By the end of the course, participants should be able to:

• Develop foundational knowledge of Recommender Systems (RecSys), including both discriminative and generative approaches
• Understand a wide variety of RecSys algorithms and their application across diverse domains, including healthcare and visual arts
• Design and evaluate human-centred RecSys, incorporating principles of user experience, ethical AI, and interdisciplinary considerations
• Apply latest advancements in Generative AI, LLMs, RAG, and LangChain for building intelligent, personalized, and interactive recommender systems in a non-technical way

Intensive week format: Theory sessions in the morning (lectures with relatable examples and visuals) and hands-on activities in the afternoon (guided Google Colab demos with pre-built templates, group brainstorming, and interactive exercises). No coding required; focus on concepts, design, and creativity.