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Learner Reviews & Feedback for Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning by DeepLearning.AI

18,179 ratings

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 upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

Top reviews


Mar 8, 2019

Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?


Nov 13, 2022

The instructor was beneficial in delivering the course in a byte-sized format. Furthermore, the problem-based approach was a bonus, because I feel like earning the certificate was definitely worth it

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3001 - 3025 of 3,757 Reviews for Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

By Kaustubh D

Jul 28, 2019

This is an excellent course to get hands-on. Keeping some tasks as repetitive like those of the callback functions help make the person strongly hands-on and remember them. Just the way, every week's programming assignment involved writing the callback function, if there would be other TF functions/methods that the coder gets to implement and override and other TF abstract classes to extend from, that would have been cherry on top!

Drilling down from the bigger picture of model definition to seemed extremely useful.

And since there are tons of courses on theory of ML and DL, thank god this one just focusses on coding it out.

By Егор Е

Aug 2, 2019

I like structure and content of this introdactory course. And like the easy and clear way Laurence Moroney told about all this stuff. Particulary, I like clear formulated exercises. During course we got great bulk of working examples in jupiter notebookes, containg full lecture, notes, likns to supporting materials!

What I would improve in course it is the change a litle bit a balance from solving problems to technical implementation. We learn a lot of using CNN for image recognition. However, it would be great to listen in more details about calculating the shape for input and outputs for layers.

By Aditya L

Aug 15, 2020

Course in concise and to the point, I was hoping to learn more about TensorFlow than Keras. It is a good course to dive into deep learning without much knowledge in data science. The instructor is motivating and explains the concepts fairly well. I want him to improve the explanation of the parameters (e.g steps_per_epoch vs epochs vs iterations) in Keras as the course is quite applied and making these explanations better will significantly improve the course. I hope to learn more TensorFlow in the next courses in the specialization. The examples were really good and explained the concepts well.

By Renee S R

Jun 24, 2020

Very good material and enjoyed the short videos, sample code, and ease of moving through the materials.

I like how it is broken into 4-weeks and the amount of effort seems appropriate.

I did experience some frustration with the exercise submission process. Seems whenever I clicked on the link to see my submission, more often than not the submission was not stored and I had to rewrite my solution multiple times. In the end, by clicking 'ok' in the submit response box (rather than the link), I had better luck, as it allowed me to return to the notebook and save it.

By Devansh K

Feb 10, 2020

I loved the instructors and the content. For the first time, I found a course that actually taught me the practical aspects of deep learning in a fun and interactive way. The content was very good and the right level of difficulty, i.e. not too difficult but also reasonably challenging. One thing I would change about the course to make it better would be to have longer instructional videos that go over all the code in more detail. I did not completely understand some sections of code and I think this would have changed if there were more code explanations.

By João A J d S

Apr 30, 2019

It's a great course! Very well structured, with an amazing amount of jupyter Notebooks (Colab) to work with, in a real hands on approach.

Just one criticism, which is why I didn't classify it as 5 Star: There isn't much of an evaluation. The tests are a bit easy, and it would be good to have at least one extensive assignment (maybe with other datasets...).

It's just that I feel the contents were really good. But if I can just pass the tests easily, I feel it doesn't really count as much of a "quality stamp" (to have passed this course).

By Jennifer J

Jul 14, 2020

Great course, however it was annoying having to "roll the dice" so to speak to get the answers right. Perhaps if it wasn't left to chance to achieve the right grades, it would of been much quicker and easier to get through. I'd say this is also a course for everyone who's had at least some experience in programming. Understanding some deep learning helps, but you definitely need knowledge of how to code in python. If you can code well in Python and are good with math, then this course would be a breeze for you!

By Jeffrey J

Aug 23, 2022

Really helpful and easy to understand. I know several programming languages but not Python, so I appreciated the labs that helped me get up to speed with Python.

The only downside is that I am not particularly interested in image classification, which is the main focus of the course. It was interesting to learn about all the convolution techniques but I doubt I will use them in practice. It would have been nice to have examples of AI problems that were not image classifcation, like a regression problem.

By Reinhard G

Jan 9, 2023

Clear explanations and the tasks, which are easy to understand, make it a really enjoyable journey to learn the depts of Machine Learning. One problem I had was following:

The assignments at the end of each week require me to go to a web-lab, to which I unfortunately couldn't connect. There was always an error which lead to the problem, that I couldn't test the code I wrote there. Therefore I had to copy all data-sets on my own working-station und try it out there and hope, it would work on the lab.

By Pawel B

Apr 14, 2020

Overall the course is nice and provided me with some skills. The main drawback is that the course does not demand large amount of student's input. If you are quite familiar with Python and have some basic ML understanding, I guess you can do it in less than 48 hours (including videos, readings and assessments). The tests can be guessed, the coding exercises are better, but also largely rely on the codes provided during the course. Having in mind this was "introduction", 4 stars.

By José D

Apr 12, 2020

Very quick and simple introduction to Neural Network using Keras's Tensorflow high-level API. Simple understandable introductory examples about how to build a neural network or Convolutional Neural Network in a few lines of code. There's no Math in this course. The downside is you won't understand how it works under the hood, and why it works (or doesn't ;-)). If you want a deeper understanding, you must study "DeepLearning Specialization" and/or "Machine Learning" course.

By Bruce B

Feb 27, 2020

A great starter course. My only suggestions:

In the code completion exercises, a note or two indicating what is expected to be done, would be helpful. You kind-of have to go back and look at the previous problems to guess what is being asked of the student.

A complete slide deck would be very helpful, if only to be able to write notes onto the slides. And it would allow the student to do less scribbling, and more pondering of the problems being discussed.

By Samuel M

Jan 23, 2020

Nice class, covers some basics of tensorflow and learns how to quickly build a NN. Not too fond of the quizzes: a few unclear question/choices and lots of "learn by heart" questions (like: what is the size of the pictures in this specific dataset, what is that specific param name) which you can easily answer without understanding too much. The assignments are simple enough for an introduction, quite close to the lesson examples but still interesting.

By Achal J

Aug 6, 2020

This course is good, and is fast paced.Mr Mororney is an excellent instructor.

The course is real good and basically focuses on CNN and ANN. The only shortcoming was that they didn't really teach 'pure' tensorflow,this course is really about Keras and not tensorflow. We are taught how to use Keras with tensorflow as backend .

They should have taught basics of tensorflow such as place holders and what are tensors!.

Nevertheless, it's a good course.

By Jeramie G

May 5, 2020

This is a great introductory course which focuses on implementing basic Keras models. The only gripe I have with this course is the programming assignments. I experienced many, many issues while trying to submit the assignments even with proposed solutions from the discussion board. This isn't a show-stopper; just a little frustrating. Otherwise, I highly recommend this course to anyone getting started withTensorFlow & Keras model building.

By Ruxue P

Sep 18, 2020

I've been an machine learning engineer for 2 years, taking this course to push myself to learn new TF2 features. I don't think there's focus on the new distributed training feature in TF2, codes are still TF1.x.

I think the last quiz had some really unclear questions, could be improved.

Other than that, I love the hands-on practice part. Wish we explain more on why model performance is so brittle in the horse vs human classification example.

By Amit K

Apr 12, 2020

Although course content seems to be nice but a regular update with the current tensorflow version needs to be done. Also, In course content there are topics listed just to tell that in next section what you will study(even provided 10 mins for that) and that is a complete waste and poorly put in the content section-this needs to be fixed.

On a positive node, this course is very useful to start and I recommended this to beginners.

By Rajesh R

Jun 2, 2020

Great review of TF and the newer tf.keras API in addition to practical advice on deep learning projects. Lawerence has been a pretty good instructor, clear and to the point, with some good exercises. For beginners, though the course skims over some of the basics - although these are covered in Andrew Ng's Deep Learning specialization, which I took some years ago. All in all, a handy course to get cracking on TF and Keras again!

By Ronet S

Feb 25, 2020

Brilliant Course for getting started with Tensorflow. The only thing I would like the instructor to include are explanation for non -TF stuff, like matplotlib codes. It would really help develop additional skills apart from making TF models. Going online to find the working of each command in a different library like matplotlib really broke my flow and my focus . So, that would be a welcome addition!

By Jim D

Sep 25, 2019

I really liked that it was very hands-on and made it very quick and easy to get up to speed on using TensorFlow for Machine Learning. That said, there was a lot less content that I expected (I finished the '4-week' course in about 1.5 days), and I was a bit disappointed that the focus was exclusively on image classification. A little variety in terms of the problems being solved would've been nice.

By Venkatesan A S

Sep 7, 2020

The course is targeted for an audience with a basic knowledge of the machine learning techniques. With that in mind, it delivers a comprehensive first look at the calibre of the TensorFlow framework. For the more advanced practitioners the programming exercises and the quiz might seem a bit on the easier side. Overall it is a great place to start for those who wish to begin with TensorFlow. Kudos!

By Miguel L

Apr 11, 2020

The contents and instructor is excellent. Unfortunately one is faced with mainly two downfalls. Fist, there always seems to be some sort of submission problem which usually involves some kind of "hacking" from the user's part to make it work. Secondly, it's very hard to get answers to most doubts since the activity in the discussion Forums is very little, specially from instructor-level sources.

By Elias B

Aug 7, 2019

Overall a very good course (with knowledge from the deep learning specialization) to get a deeper knowledge in tensorflow. But sometimes in the exercises you feel a little left alone, because of missing information (example Week 4, which folder should you use, what's the resolution of the images, you can find out but that requiered (for me I had to downloaded the files and check what i needed).

By Brian F

Feb 2, 2021

Great course giving a very basic overview of some features of Tensor Flow. The assignments could be implemented a little bit better, there were a lot of version issues relating to tensor flow.

Also, the course would benefit from moderation of the discussion forums. Overall very happy with my experience however and would recommend for anyone looking to get started in machine learning.

By VizLore R

Dec 22, 2021

The only reason I'm not giving it 5 stars is because I think some concepts could be explained in more details, such as batch_size and number of filters. Maybe that will be covered in the next courses in this specialization, and if that turns out to be the case, I'll change the rating to 5 stars. Generally, excellent teachers and able to explain complex topics in a simple manner.