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Basic Recommender Systems
Learn key approaches in recommender systems. Master collaborative and content-based techniques for effective recommendations.
Course Cost
₹ 2,699
Intermediate
Skill Level
10 Hours
Self-paced lessons
This course introduces you to leading approaches in recommender systems, covering both collaborative and content-based techniques. You'll learn how these systems work, how to use them, and how to evaluate their performance. The course equips you with tools to measure recommender system quality and improve it through new algorithm design. You'll explore ethical considerations like identity, privacy, and manipulation. By the end, you'll be able to describe recommender system requirements for different domains, distinguish systems by input data and mechanisms, and design tailored systems for new applications.
3,376 Enrolled
English
What you'll learn
Build a basic recommender system
Choose appropriate recommender system types based on input data and goals
Identify correct evaluation methods for measuring recommender system quality
Understand benefits and limitations of different recommender techniques
Apply collaborative and content-based filtering approaches
Design recommender systems for new application domains
Consider ethical issues in recommender system development
Use creativity and innovation to improve recommendation quality
Skills you'll gain
This course includes:
123 Minutes PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This course provides a comprehensive introduction to recommender systems, covering the leading approaches in both collaborative and content-based techniques. Students will learn how these systems work, how to implement them, and how to evaluate their performance. The curriculum covers the most important algorithms used in recommender systems, teaching students to distinguish between different types based on input data, internal mechanisms, and goals. Practical skills in measuring and improving recommender system quality are emphasized, along with the ability to design systems for new application domains. The course also addresses important ethical considerations in recommender system design, including issues of identity, privacy, and manipulation.
BASIC CONCEPTS
Module 1 · 2 Hours to complete
EVALUATION OF RECOMMENDER SYSTEMS
Module 2 · 2 Hours to complete
CONTENT-BASED FILTERING
Module 3 · 3 Hours to complete
COLLABORATIVE FILTERING
Module 4 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Frequently asked Questions
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