The Complete Recommender Systems Masterclass - Build 7 Projects

Learn how to snag the most in demand role in the tech field today!

We'll cover tried and true recommendation algorithms based on neighborhood-based collaborative filtering, and work our way up to more modern techniques including matrix factorization and even deep learning with artificial neural networks. Along the way, you'll learn from our extensive industry experience to understand the real-world challenges you'll encounter when applying these algorithms at large scale and with real-world data.


Your Instructor


Alexandra Kropf
Alexandra Kropf

Alexandra Kropf is Mammoth Interactive's CLO and a software developer with extensive experience in full-stack web development, app development and game development. She has helped produce courses for Mammoth Interactive since 2016, including the Coding Interview series in Java, JavaScript, C++, C#, Python and Swift.

Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more.

Over 12 years, Mammoth Interactive has built a global student community with 4 million courses sold. Mammoth Interactive has released over 350 courses and 3,500 hours of video content.

Founder and CEO John Bura has been programming since 1997 and teaching since 2002. John has created top-selling applications for iOS, Xbox and more. John also runs SaaS company Devonian Apps, building efficiency-minded software for technology workers like you.


Course Curriculum


  00a Introduction to Recommender Systems
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  00c Introduction to Python (Prerequisite)
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  01 Build a Basic Movie Recommender System
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  02 Projects 2 and 3 Preview - Machine Learning Movie Recommender
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  03 Machine Learning Fundamentals
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  04 Introduction to User Similarity
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  05 Recommend a Movie Based on User Similarity
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  06 Recommend a Movie with a K Nearest Neighbors Classifier
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  07 Project 4 Preview - Complex Machine Learning Recommender
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  08 Data Processing Profiles and Items
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  09 Build Models for User Recommendations
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  10 Build a Model to Predict Ratings
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  11 Deep Learning Fundamentals
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  12 Build a Neural Network to Predict Ratings
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  13 Data Analysis with Pandas, Numpy and Sci-kit Learn
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Frequently Asked Questions


When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

Get started now!