Custom and Distributed Training with TensorFlow
DeepLearning.AI · View on Coursera ↗
Taught by Laurence Moroney, Eddy Shyu
Data ScienceComputer Science
About the course
In this course, you will: • Learn about Tensor objects, the fundamental building blocks of TensorFlow, understand the difference between the eager and graph modes in TensorFlow, and learn how to use a TensorFlow tool to calculate gradients. • Build your own custom training loops using GradientTape and TensorFlow Datasets to gain more flexibility and visibility with your model training. • Learn about the benefits of generating code that runs in graph mode, take a peek at what graph code looks li
The dissent
The most-upvoted critical review (1 vote, 3.0★).
“week 1 and 2 were great - full of many interesting information week 3 and 4 were quite boring thus hard to struggle and get valuable knowledge”
Coursera's 4.8 comes from 439 ratings. Of those, 1.6% 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 23 Oct 2026.Read them on Coursera ↗