Coursera

Recommender Systems (Coursera)

Offered by Sungkyunkwan University - SKKU,
Recommender Systems (Coursera)

In this course you will: a) understand the basic concept of recommender systems; b) understand the Collaborative Filtering; c) understand the Recommender System with Deep Learning; d) understand the Further Issues of Recommender Systems. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, conditional probability, and basic machine learning algorithms.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

What You Will Learn

  • Understand the basic concept of recommender systems.
  • Understand the Collaborative Filtering.
  • Understand the Recommender System with Deep Learning.
  • Understand the Further Issues of Recommender Systems.

Syllabus

WEEK 1 : Introduction to Recommender Systems
WEEK 2: Collaborative Filtering
WEEK 3: Recommender System with Deep Learning
WEEK 4: Further Understanding of Recommender Systems

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

AI Capstone Project with Deep Learning (Coursera) Coursera
IBM

AI Capstone Project with Deep Learning (Coursera)

Data Science

In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They will load and pre-process data for a real problem, build the model and validate it. Learners will then present a project report to demonstrate the validity of their model and their proficiency in the field of Deep Learning.

Aug 3rd 2026
4 Weeks
Artificial Intelligence Machine Learning Knowledge
Details
AI Strategy and Governance (Coursera) Coursera
University of Pennsylvania

AI Strategy and Governance (Coursera)

Data Science

In this course, you will discover AI and the strategies that are used in transforming business in order to gain a competitive advantage. You will explore the multitude of uses for AI in an enterprise setting and the tools that are available to lower the barriers to AI use. You will get a closer look at the purpose, function, and use-cases for explainable AI. This course will also provide you with the tools to build responsible AI governance algorithms as faculty dive into the large datasets that you can expect to see in an enterprise setting and how that affects the business on a greater scale.

Aug 3rd 2026
4 Weeks
Artificial Intelligence Governance Deep Learning
Details
Search Engines for Web and Enterprise Data (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Search Engines for Web and Enterprise Data (Coursera)

CS: Software Engineering

This course introduces the technologies behind web and search engines, including document indexing, searching and ranking. You will also learn different performance metrics for evaluating search quality, methods for understanding user intent and document semantics, and advanced applications including recommendation systems and summarization. Real-life examples and case studies are provided to reinforce the understanding of search algorithms.

Aug 17th 2026
13-24 Weeks
Web Recommender Systems Web Search
Details
Deep Learning and Reinforcement Learning (Coursera) Coursera
IBM

Deep Learning and Reinforcement Learning (Coursera)

Data Science

This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning.

Aug 3rd 2026
5-12 Weeks
Calculus Python Statistics
Details
Sequence Models (Coursera) Coursera
DeepLearning.AI

Sequence Models (Coursera)

Data Science

This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others.

Aug 3rd 2026
3 Weeks
Machine Learning Deep Learning Artificial Neural Networks
Details
Technologies and platforms for Artificial Intelligence (Coursera) Coursera
Politecnico di Milano

Technologies and platforms for Artificial Intelligence (Coursera)

Robotics & Computer Vision

This course will address the hardware technologies for machine and deep learning (from the units of an Internet-of-Things system to a large-scale data centers) and will explore the families of machine and deep learning platforms (libraries and frameworks) for the design and development of smart applications and systems.

Aug 17th 2026
4 Weeks
Artificial Intelligence Cloud Machine Learning
Details
Deep Learning for Business (Coursera) Coursera
Yonsei University

Deep Learning for Business (Coursera)

Management & Leadership

Your smartphone, smartwatch, and automobile (if it is a newer model) have AI (Artificial Intelligence) inside serving you every day. In the near future, more advanced “self-learning” capable DL (Deep Learning) and ML (Machine Learning) technology will be used in almost every aspect of your business and industry. So now is the right time to learn what DL and ML is and how to use it in advantage of your company. This course has three parts, where the first part focuses on DL and ML technology based future business strategy including details on new state-of-the-art products/services and open source DL software, which are the future enablers.

Jul 27th 2026
5-12 Weeks
Business ML Artificial Intelligence
Details
Customising your models with TensorFlow 2 (Coursera) Coursera
Imperial College London

Customising your models with TensorFlow 2 (Coursera)

Data Science

Welcome to this course on Customising your models with TensorFlow 2! In this course you will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. You will use lower level APIs in TensorFlow to develop complex model architectures, fully customised layers, and a flexible data workflow. You will also expand your knowledge of the TensorFlow APIs to include sequence models.

Aug 3rd 2026
5-12 Weeks
Machine Learning Modeling APIs
Details
Basic Recommender Systems (Coursera) Coursera
EIT Digital

Basic Recommender Systems (Coursera)

Statistics & Data Analysis Data Science

This course introduces you to the leading approaches in recommender systems. The techniques described touch both collaborative and content-based approaches and include the most important algorithms used to provide recommendations. You'll learn how they work, how to use and how to evaluate them, pointing out benefits and limits of different recommender system alternatives.

Aug 3rd 2026
4 Weeks
Algorithms Matrix Systems
Details
Practical Machine Learning on H2O (Coursera) Coursera
H2O.ai

Practical Machine Learning on H2O (Coursera)

Data Science

In this course, we will learn all the core techniques needed to make effective use of H2O. Even if you have no prior experience of machine learning, even if your math is weak, by the end of this course you will be able to make machine learning models using a variety of algorithms. We will be using linear models, random forest, GBMs and of course deep learning, as well as some unsupervised learning algorithms.

Aug 17th 2026
5-12 Weeks
Machine Learning Data Science Linear Models
Details