Curious about how platforms like Netflix and Amazon know just what you might like next? Join our webinar, Getting Started with Recommendation Systems, where we'll break down the basics of these smart systems and their role in personalizing your experience. Explore how recommendation algorithms analyze user data to make personalized suggestions, and learn how you can apply these principles to your own projects. Perfect for both beginners and those interested in data-driven solutions, this session offers a practical introduction to building recommendation engines that add value to any business or user platform.
Agenda for the session
- Core Principles of Recommendation Systems
- Building Basic Recommendation Algorithms
- MIT PE's Applied Data Science Program
- Live Q&A
About Speakers
Nitin Sethi
Analytics Team Lead, Rio Tinto
Nitin Sethi is a data science and analytics professional with more than 15 years of experience in building advanced analytical models with Python and SPSS. Currently working as a Senior Advisor at Rio Tinto, Nitin has extensive experience using analytics and data science to solve problems across various industries.
MIT Professional Education's Applied Data Science Program
The Applied Data Science Program curriculum has been carefully crafted by MIT faculty to provide you with the skills, knowledge, and confidence you need to flourish in the industry. By encompassing the most business-relevant technologies, such as Machine Learning, Deep Learning, Recommendation Systems, and more, it prepares you to be an important part of data science efforts at any organization.
