Overview
Recommender systems have been widely used by online shopping companies. They play a critical role in analysing customer transactions and web browsing behaviours to provide sound recommendations for their customers, contributing to sales revenue and profitability. In this regard, a reliable and efficient recommendation system is essential for many companies’ market and business success.
Course Description & Learning Outcomes
This course is part of the Data Science and Graduate Certificate in Business Analytics Practice Series offered by NUS-ISS. At the end of the course, the participants will be able to: - Understand the role and applications of recommendation systems - Identify the types of data necessary for building a recommendation system - Understand the main types of recommender system and be able to decide when each should be used - Build recommendation systems using statistical modelling - Enhance recommendation systems based on testing and validation
Recommended Prerequisites
This is an intensive, advanced course. It contains workshops that are conducted using python and basic knowledge of the python language is required. You will be required to pass a pre-course assessment to ensure that you have the requisite background knowledge to learn the material. This assessment is waived if you have completed the course: Statistics Bootcamp II.
Pre-course instructions
- No printed copies of course materials are issued. - Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials. Registration close date: 25/12/2023
Schedule
Date: 15 Jan 2024, Monday
Time: 12:00 AM - 12:00 AM (GMT +8:00) Kuala Lumpur, Singapore
Location: NUS-ISS, 25 Heng Mui Keng Terrace, 119615
Pricing
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