Convolutional Neural Networks in TensorFlow
DeepLearning.AI · View on Coursera ↗
Taught by Laurence Moroney
Data ScienceComputer Science
About the course
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 DeepLearning.AI TensorFlow Developer Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 2 of the DeepLearning.AI TensorFlow Developer Specialization, you will learn advanced techniques to improve the computer vision model you built in Course 1. Y
The dissent
The most-upvoted critical review (75 votes, 1.0★).
“This course significantly lacks depth. The topic is covered at a very high-level and represents only a lightweight introduction. You will not gain any insights into the challenges that someone might face using CNNs on Tensorflow in a real-world scenario.”
Coursera's 4.7 comes from 8,226 ratings. Of those, 1.8% are 1–2★.
Starisk reads the reviews learners voted most helpful, and weights each by the square root of its votes: a review with 80 upvotes counts about five times one with 2. Unvoted reviews are not skipped out of laziness — by this model they carry no evidence that other students endorsed them.
That measures what the most-endorsed reviews say, not “true quality.” The rating distribution above is the whole population, so you can see the sample next to it.
Reviews read on 22 Oct 2026.Read them on Coursera ↗