What are recommender systems?

Recommender systems are processes that information filtering systems use to identify and predict the amount of interest a user is likely to have in items. Recommender systems then suggest those items that are the most likely to be well received by the user. These systems are mainly used in commercial or retail settings, to show potential customers what previous customers with similar interests also viewed or purchased. The goal of using a recommender system is to increase sales by showing users the items they're most likely to want.

Why is it important to learn about recommender systems?

When you learn about recommender systems, you can become more valuable to your employer by helping to increase sales by applying this deep-learning tactic. It can help you become more data literate as a professional in the field of marketing. If you enjoy advanced mathematics or building spreadsheets, learning about recommender systems may prove especially satisfying to you because it involves using algorithms and spreadsheets. Learning how to program recommender systems is important for IT teams and website builders working for commercial companies.

What career opportunities can arise from learning recommender systems?

Learning about recommender systems can help you launch a new career in data science or in the IT field. You could work for large companies that want to keep visitors on their sites as long as possible by offering products, music, or videos that site users are likely to appreciate based on previous behaviors. Other career fields you could enter after adding recommender systems to your educational portfolio include data science, data mining, machine learning, and artificial intelligence (AI).

How can taking online courses on Coursera help me learn recommender systems?

Taking courses on Coursera can help you learn about recommender systems by introducing the information at your current level of study, so you are challenged enough to find the learning exciting. It can also help because you get to progress through the recommender systems courses while covering topics, such as TensorFlow and collaborative filtering, at your own pace on Coursera, so you can finish as quickly or as slowly as you need to thoroughly absorb the material.

What are the benefits of taking an online Recommender Systems course?

Online Recommender Systems courses offer a convenient and flexible way to enhance your knowledge or learn new Recommender Systems skills. Choose from a wide range of Recommender Systems courses offered by top universities and industry leaders tailored to various skill levels.

What Recommender Systems courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Recommender Systems, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Top Recommender Systems Courses - Learn Recommender Systems Online

Explore the Recommender Systems Course Catalog

Status: Free Trial
University of Minnesota
Recommender Systems
Skills you'll gain: AI Personalization, Machine Learning Algorithms, Taxonomy, Applied Machine Learning, Machine Learning, Dimensionality Reduction, Performance Metric, Spreadsheet Software, Performance Measurement, Benchmarking, Usability Testing, Exploratory Data Analysis, A/B Testing, Analysis, User Feedback, Algorithms, System Design and Implementation, Solution Design, Data-Driven Decision-Making, Predictive Modeling
4.3
Rating, 4.3 out of 5 stars
827 reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
DeepLearning.AI
Unsupervised Learning, Recommenders, Reinforcement Learning
Skills you'll gain: Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Supervised Learning, Artificial Intelligence, Reinforcement Learning, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms
4.9
Rating, 4.9 out of 5 stars
5.2K reviews
Beginner · Course · 1 - 4 Weeks
Status: New
Status: Free Trial
University of Colorado System
AI for Healthcare Systems
Skills you'll gain: Responsible AI, Agentic systems, Data Ethics, Machine Learning Algorithms, Data Governance, Health Systems, Health Informatics, Artificial Intelligence, Analytics, Digital Transformation, Healthcare Industry Knowledge, Healthcare Ethics, Artificial Intelligence and Machine Learning (AI/ML), Human Factors (Security), Generative AI Agents, Machine Learning, Health Technology, Health Information Management, Information Technology, Information Systems
Beginner · Specialization · 3 - 6 Months
Status: New
Status: Free Trial
IBM
Building AI Agents and Agentic Workflows
Skills you'll gain: LangChain, Tool Calling, LangGraph, LLM Application, Agentic systems, Generative AI Agents, Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Application Design, Prompt Engineering, Large Language Modeling, Collaborative Software, Application Development, Software Design Patterns, System Design and Implementation, Software Development, Python Programming, Real Time Data, Data Science
4.9
Rating, 4.9 out of 5 stars
57 reviews
Intermediate · Specialization · 1 - 3 Months
Status: Free Trial
Packt
Recommender Systems Complete Course Beginner to Advanced
Skills you'll gain: Tensorflow, PyTorch (Machine Learning Library), Natural Language Processing, Deep Learning, Predictive Modeling, Time Series Analysis and Forecasting, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms, Data Analysis
Intermediate · Course · 1 - 4 Weeks
EIT Digital
Basic Recommender Systems
Skills you'll gain: Data Ethics, AI Personalization, System Requirements, Responsible AI, Machine Learning Algorithms, Innovation, Algorithms, Unsupervised Learning, Quality Assurance, Data-Driven Decision-Making, Applied Machine Learning, Performance Tuning
4.3
Rating, 4.3 out of 5 stars
43 reviews
Intermediate · Course · 1 - 4 Weeks

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Status: Preview
Sungkyunkwan University
Recommender Systems
Skills you'll gain: Scalability, Deep Learning, Applied Machine Learning, Data Mining, Data Processing, Machine Learning, Machine Learning Algorithms, Algorithms, Artificial Neural Networks, Data Structures
Intermediate · Course · 1 - 4 Weeks
Status: New
Status: Free Trial
EDUCBA
Mastering Recommendation Systems with Python
Skills you'll gain: Feature Engineering, AI Personalization, Data Processing, Applied Machine Learning, Data Manipulation, Data Science, Machine Learning, Data Cleansing, Scalability, Python Programming, Data Transformation, Pandas (Python Package), Predictive Analytics, Predictive Modeling, Text Mining, Development Environment, Unstructured Data, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Data Integration
4.7
Rating, 4.7 out of 5 stars
55 reviews
Intermediate · Specialization · 1 - 3 Months
Status: Free Trial
IBM
IBM AI Engineering
Skills you'll gain: Prompt Engineering, Large Language Modeling, PyTorch (Machine Learning Library), Unsupervised Learning, Generative AI, Keras (Neural Network Library), Supervised Learning, Reinforcement Learning, Regression Analysis, LLM Application, Scikit Learn (Machine Learning Library), Deep Learning, Applied Machine Learning, Generative AI Agents, Natural Language Processing, Tensorflow, Predictive Modeling, Machine Learning, Python Programming, Data Science
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
21K reviews
Intermediate · Professional Certificate · 3 - 6 Months
Status: Free Trial
Multiple educators
Machine Learning
Skills you'll gain: Unsupervised Learning, Supervised Learning, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Responsible AI, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming
4.9
Rating, 4.9 out of 5 stars
36K reviews
Beginner · Specialization · 1 - 3 Months
Status: Free Trial
University of Minnesota
Introduction to Recommender Systems: Non-Personalized and Content-Based
Skills you'll gain: Taxonomy, AI Personalization, Spreadsheet Software, Machine Learning, Predictive Analytics, Microsoft Excel, Statistical Methods, Persona Development, Text Mining, Descriptive Statistics, Data Collection, Algorithms, Computer Programming, Java
4.4
Rating, 4.4 out of 5 stars
654 reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
University of Minnesota
Recommender Systems: Evaluation and Metrics
Skills you'll gain: Performance Metric, Performance Measurement, Benchmarking, Usability Testing, A/B Testing, User Feedback, Analysis, Data-Driven Decision-Making, Predictive Analytics, Diversity and Inclusion
4.4
Rating, 4.4 out of 5 stars
235 reviews
Mixed · Course · 1 - 3 Months