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Learner Reviews & Feedback for Sequences, Time Series and Prediction by DeepLearning.AI

3,947 ratings
633 reviews

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 Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real-world data! 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 21, 2020

Really like the focus on practical application and demonstrating the latest capability of TensorFlow. As mentioned in the course, it is a great compliment to Andrew Ng's Deep Learning Specialization.

Jun 6, 2020

I really enjoyed this course, especially because it combines all different components (DNN, CONV-NET, and RNN) together in one application. I look forward to taking more courses from

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476 - 500 of 631 Reviews for Sequences, Time Series and Prediction

By Yingnan X

Oct 28, 2019

The homework exercise seems to heavily overlap with the demo notebook that I can simply copy and paste the code into the exercise notebook. It would be great if in the future the exercise can be a little harder and involve more thinking.

By Shiladitya P

Mar 19, 2020

I learned the best practices for forecasting using statistical techniques as well as deep learning networks in this course. One point for improvement is to focus on a few multi-variate examples with code, which was absent in the course.

By Adnan D

Dec 7, 2020

It was good totally, but I think the assignments weren't enough also I expected the multivariate time series to be covered but it wasn't, I'm waiting to see this teacher next course soon I wish for better assignments and a cool topic!

By Александр З

Oct 1, 2019

I would like to have more info on window and batch sizes - seems to be pretty important values to work with, but they are not covered in depth.

In general, greate course that shows how to prepare sequences, feed them in to NN.

Loved it.

By Vahid N

Jan 19, 2020

It is very easy to follow this course. I wish some function/object options and arguments (such as why we use Y^hat (hat is usually reserved for estimated values) and not Y in LSTMs) were explained in more detail for curious readers.

By Neelkanth S M

Nov 27, 2020

As with an machine/ deep learning model, data preprocessing is the most underrated part. Taking this course exposes students to various pre-processing nuances that are helpful in training a deep learning model.

By Tobias L

Nov 12, 2020

Nice and short introduction to time series handling in Keras. As with the other courses, this is a simple hands-on course. I therefore recommend to take the DeepLearning Specialization before this course.


Jul 17, 2020

The course is fantastic. It was a bit short and with some hyperparameters tuning focus, it could have been great. Also, it seems that it is biased to show that LSTM is always superior to RNN networks.

By mehryar m

Dec 27, 2019

I'm so glad to take this course and build my knowledge regarding time-series data and modern approaches to create prognostic models. Thanks to Andrew Ng and L. Moroney to provide this course.

By Siddhartha P

Mar 27, 2020

Few hands on programming assignments could be better for experience as was the case with starting two courses. Overall good course and the structure was well laid. Thanks for building it up

By William G

Aug 16, 2019

Though I feel some aspects of this course did not delve deep enough into the explanations of some functions, the course helped me understand how to use models for time series problems.

By hm s

Jul 19, 2020

I wish there were more detail explanation about hyper-parameter tuning when we define NN Models.

other than that, this course was great and gave me lot of insights. Thank you.

By Yongqing X

Sep 26, 2020

I'd like to learn more about algorithmic principle(Although some Andrew‘s class link is attached. )why not explain the principle combined with the real example


Aug 19, 2019

Wish there were graded programming exercises. The quizzes has questions not relevant to the goal of the lesson ex What is the seasonality of sunspots.


May 16, 2020

New techniques were learnt regarding how to create a time-series signal and how they can be manipulated for forcasting and feeding to DNN networks.

By Parth A

Aug 11, 2019

A good intro course to time series prediction. Would have loved some more data analysis and other time series methods like ARIMA and seasonal ARIMA

By Ruben Y Q

May 6, 2020

course is good but it dont get deeper on using things like multivariate time series, in addition the course practice materials where kind of lax

By Jessie S

Aug 12, 2019

A little bit too simple cuz it only covers univariate time series practice. Would be better if there's more multivariate time series exercise.

By Dan R

May 13, 2020

I was really waiting to predict 100 data that was similar to sequence, that being said; this was a good introduction to time series analysis.

By Kartik P

Oct 5, 2020

its a nice course but instead of using synthetic data, it would have been better if we use real-time datasets for our practice and learning.


May 26, 2020

The programming exercise should not have been optional. But overall, this was an amazing course. A thumbs up from my side. Thanks a lot.

By Ruben A M

Sep 9, 2020

A lot of typos and I felt that making the Graded Exercises instead of Non Graded is a much better experience for us the students.

By Erik J J D B

Jul 19, 2020

Good and easy to follow course to learn tensorflow. You need a background on Machine Learning to fully benefit from this course.


Feb 12, 2021

It is nice in introduction to the use of TF in time series. But a bit difficult in the code which without detail explanation.