Building Recommender Systems with Machine Learning and AI
★ 4.4 rated · $11.99
The most in-depth course on recommendation systems with deep learning, machine learning, data science, and AI techniques
$10.99 with coupon (list $149.99 — save $139.00, 93% off)
Coupon Verified: May 31, 2026 · click Claim Coupon to apply the discount code
Our verdict: worth it — as long as the Business skills on the syllabus match what you actually want to learn. The regular price for Recommender Systems and Deep Learning in Python on Udemy is $149.99. With the coupon code on this page, that falls to $10.99 — a saving of $139.00, or 93% off the standard rate Spread across 13h of on-demand video, that works out to roughly $0.85 per hour of content — cheaper than a single chapter of most printed Business textbooks.
A cheap price means nothing if the material is thin — here the syllabus is organized around usable outcomes. Lazy Programmer Team and Lazy Programmer Inc. walk you through understand and implement accurate recommendations for your users using simple and state-of-the-art algorithms, big data matrix factorization on Spark with an AWS EC2 cluster, and matrix factorization / SVD in pure Numpy — skills meant to be used, not just watched. It has already been taken by 35,862 students and holds a 4.7-star average from verified reviews, which suggests the content holds up once learners actually apply it.
Check the prerequisites before you commit: For earlier sections, just know some basic arithmetic; For advanced sections, know calculus, linear algebra, and probability for a deeper understanding. Best suited to learners who already have footing in Business. Plan for roughly 13h of on-demand video at your own pace. Lessons are delivered in English.
Practical skills and outcomes you'll gain from Recommender Systems and Deep Learning in Python — taken from the official Udemy syllabus for Business learners.
Understand and implement accurate recommendations for your users using simple and state-of-the-art algorithms.
Big data matrix factorization on Spark with an AWS EC2 cluster.
Matrix factorization / SVD in pure Numpy.
Matrix factorization in Keras.
Deep neural networks, residual networks, and autoencoder in Keras.
Restricted Boltzmann Machine in Tensorflow.
What you need before enrolling in Recommender Systems and Deep Learning in Python — prerequisites as listed by the instructor on Udemy.
For earlier sections, just know some basic arithmetic
For advanced sections, know calculus, linear algebra, and probability for a deeper understanding
Be proficient in Python and the Numpy stack (see my free course)
For the deep learning section, know the basics of using Keras
The full official description of Recommender Systems and Deep Learning in Python — curriculum, teaching approach, and everything included with this Udemy coupon.
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Common queries about this coupon, pricing, and enrollment. Answers reflect our last check on May 31, 2026.
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