Recommender Systems (Coursera)

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

Machine Learning Foundations for Product Managers (Coursera) Coursera
Duke University

Machine Learning Foundations for Product Managers (Coursera)

In this first course of the AI Product Management Specialization offered by Duke University's Pratt School of Engineering, you will build a foundational understanding of what machine learning is, how it works and when and why it is applied. To successfully manage an AI team or product and work collaboratively with data scientists, software engineers, and customers you need to understand the basics of machine learning technology.

Nov 9th 2026
5-12 Weeks
Customising your models with TensorFlow 2 (Coursera) Coursera
Imperial College London

Customising your models with TensorFlow 2 (Coursera)

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.

Nov 9th 2026
5-12 Weeks
Introduction to Recommender Systems: Non-Personalized and Content-Based (Coursera) Coursera
University of Minnesota

Introduction to Recommender Systems: Non-Personalized and Content-Based (Coursera)

This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations.

Nov 9th 2026
4 Weeks
Text Retrieval and Search Engines (Coursera) Coursera
University of Illinois at Urbana-Champaign

Text Retrieval and Search Engines (Coursera)

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.

Nov 9th 2026
5-12 Weeks
Neural Networks and Deep Learning (Coursera) Coursera
DeepLearning.AI

Neural Networks and Deep Learning (Coursera)

If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago. In this course, you will learn the foundations of deep learning.

Nov 9th 2026
4 Weeks
AI Capstone Project with Deep Learning (Coursera) Coursera
IBM

AI Capstone Project with Deep Learning (Coursera)

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.

Nov 9th 2026
4 Weeks
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera) Coursera
DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Nov 9th 2026
4 Weeks
Deep Learning and Reinforcement Learning (Coursera) Coursera
IBM

Deep Learning and Reinforcement Learning (Coursera)

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.

Nov 9th 2026
5-12 Weeks
Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (Coursera) Coursera
University of Illinois at Urbana-Champaign

Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (Coursera)

Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information.

Nov 9th 2026
4 Weeks
Sequence Models (Coursera) Coursera
DeepLearning.AI

Sequence Models (Coursera)

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.

Nov 9th 2026
3 Weeks
Structuring Machine Learning Projects (Coursera) Coursera
DeepLearning.AI

Structuring Machine Learning Projects (Coursera)

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience.

Nov 9th 2026
2 Weeks