Ziga Inc is seeking to enhance its user experience by developing a recommendation system that leverages user data to provide personalized content suggestions. The goal of this project is to design a prototype recommendation system that can analyze user behavior and preferences to deliver tailored recommendations. This project will allow learners to apply their knowledge of data analysis, machine learning algorithms, and software development. The system should be capable of processing user data, identifying patterns, and suggesting relevant content. The project will focus on creating a scalable and efficient system that can be integrated into Ziga Inc's existing platform. Learners will work collaboratively to ensure the system meets the specified requirements and provides accurate recommendations.

- A detailed report outlining the design and architecture of the recommendation system.

- A working prototype of the recommendation system capable of processing sample user data.

- Documentation of the algorithms used and the rationale behind their selection.

- A presentation demonstrating the system's functionality and potential impact on user engagement.