Lilly Tech Systems
AI Personalization Engines
Build real-time personalization systems that adapt content, recommendations, and experiences to each individual user. Master the algorithms, architectures, and strategies behind modern AI-driven personalization at scale.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Personalization fundamentals: from segments to individuals, and why AI makes true 1:1 personalization possible at scale.
2. Data Signals
Collecting and unifying behavioral, contextual, and preference data to power real-time personalization decisions.
3. Algorithms
Collaborative filtering, content-based, contextual bandits, and deep learning models for personalization.
4. Content Adaptation
Dynamic content generation, adaptive layouts, personalized messaging, and AI-driven creative optimization.
5. Real-Time Systems
Architecture for sub-100ms personalization decisions: feature stores, model serving, and edge computing.
6. Privacy & Ethics
Privacy-preserving personalization, consent management, filter bubbles, and responsible AI practices.
What You'll Learn
By the end of this course, you'll be able to:
Personalize in Real Time
Build systems that deliver individualized experiences in milliseconds based on real-time user behavior and context.
Choose Algorithms
Select the right personalization algorithm for each use case, from collaborative filtering to contextual bandits.
Adapt Content
Dynamically generate and adapt content, layouts, and messaging for each individual user across channels.
Respect Privacy
Implement personalization that respects user privacy, complies with regulations, and maintains ethical standards.