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Recommender Systems Courses

Recommender systems courses can help you learn collaborative filtering, content-based filtering, and hybrid approaches to personalization. You can build skills in data analysis, user behavior modeling, and algorithm evaluation. Many courses introduce tools like Python libraries such as Scikit-learn and TensorFlow, that support implementing machine learning algorithms, as well as frameworks for managing large datasets and user interactions.


Popular Recommender Systems Courses and Certifications


  • Status: Free Trial
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    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
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    830 reviews

    Intermediate · Specialization · 3 - 6 Months

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    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
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    5.4K reviews

    Beginner · Course · 1 - 4 Weeks

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    LearnQuest

    Build and Deploy Chatbots and Recommender Systems

    Skills you'll gain: Responsible AI, No-Code Development, LLM Application, ChatGPT, Business Metrics, Data Ethics, AI Personalization, Return On Investment, Application Deployment, Artificial Intelligence, AI Product Strategy, Customer experience improvement, Language Interpretation, Translation, and Studies, Performance Measurement, Key Performance Indicators (KPIs), Continuous Improvement Process, Natural Language Processing, Business Ethics, User Feedback, Customer Engagement

    Beginner · Course · 1 - 4 Weeks

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    LearnQuest

    Decision-Making in Dynamic Environments

    Skills you'll gain: Reinforcement Learning, Responsible AI, Agentic systems, Data Ethics, Artificial Intelligence, Machine Learning Methods, Distributed Computing, Simulations

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    U

    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
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    235 reviews

    Mixed · Course · 1 - 3 Months

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    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

What brings you to Coursera today?

  • Status: New
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    Packt

    Recommender Systems

    Skills you'll gain: AI Personalization, Data Manipulation, Apache Spark, Tensorflow, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Natural Language Processing, AWS SageMaker, Scalability, Applied Machine Learning, Data Processing, Supervised Learning, Dimensionality Reduction, Machine Learning, Pandas (Python Package), Predictive Modeling, Python Programming, Time Series Analysis and Forecasting, Artificial Neural Networks

    Intermediate · Specialization · 3 - 6 Months

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    S

    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
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    37K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: New
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    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, Machine Learning Algorithms, Python Programming, Data Transformation, Pandas (Python Package), Predictive Analytics, Predictive Modeling, Text Mining, Development Environment, Unstructured Data, Scikit Learn (Machine Learning Library), Data Integration

    4.7
    Rating, 4.7 out of 5 stars
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    58 reviews

    Intermediate · Specialization · 1 - 3 Months

  • E

    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
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    43 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
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    S

    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: Free Trial
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    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, PyTorch (Machine Learning Library), Computer Vision, Unsupervised Learning, Generative AI, PySpark, Keras (Neural Network Library), Supervised Learning, Deep Learning, Reinforcement Learning, Regression Analysis, LLM Application, Scikit Learn (Machine Learning Library), Applied Machine Learning, Natural Language Processing, Machine Learning, Python Programming, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    21K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

Searches related to recommender systems

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1234…424

In summary, here are 10 of our most popular recommender systems courses

  • Recommender Systems: University of Minnesota
  • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
  • Build and Deploy Chatbots and Recommender Systems: LearnQuest
  • Decision-Making in Dynamic Environments: LearnQuest
  • Recommender Systems: Evaluation and Metrics: University of Minnesota
  • Recommender Systems Complete Course Beginner to Advanced: Packt
  • Recommender Systems: Packt
  • Machine Learning: DeepLearning.AI
  • Mastering Recommendation Systems with Python: EDUCBA
  • Basic Recommender Systems: EIT Digital

Skills you can learn in Probability And Statistics

R Programming (19)
Inference (16)
Linear Regression (12)
Statistical Analysis (12)
Statistical Inference (11)
Regression Analysis (10)
Biostatistics (9)
Bayesian (7)
Logistic Regression (7)
Probability Distribution (7)
Bayesian Statistics (6)
Medical Statistics (6)

Frequently Asked Questions about 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.‎

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.‎

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).‎

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.‎

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.‎

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.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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