Apr 26, 2018
It was really great learning with coursera and I loved the course. The way faculty teaches here is just awesome as they are very much clear and helped a lot while learning this coursea
Jun 14, 2020
The course was amazing however I'm yet to receive my badge from IBM even after completing the course. Would really appreciate if Coursera support could assist me with this.
By Thomas B•
Mar 21, 2020
This is a good course with good introductory material that covers a broad range of topics.
By Chandan C•
Feb 09, 2020
Exercises let me explore the topic further which was very helpful for my learning
By Sourastra N•
Jul 26, 2019
The course needs to allow the students to build their own model.
By Dmitry G•
Jul 19, 2018
Concise intro to much needed big data machine learning solutions
By Victor d O•
Jan 09, 2019
I think we need in this module more pratical assignments.
By PRASHANT K R•
Jun 07, 2018
very nice course it gives more insight to deep learning.
By Jair M•
May 22, 2019
Some videos are missing, but anyway is a great course
By Amalka W•
Dec 29, 2019
Course covers scalerble deep learning concepts
By Andrey O•
Sep 07, 2018
Part with DeepLearning4J is not very good...
By Vinayak B•
Jul 30, 2019
Really Helpful course for AI Enthusiasts
By Mobassir H•
Apr 22, 2020
pytorch instructor was the best <3
By Valerio N•
Mar 27, 2019
Very Complete course.
By Arati Y•
Apr 09, 2018
It was nice
By Tobias H•
Aug 26, 2018
By Pierre-Matthieu P•
Nov 30, 2019
I was pretty disppointed overall.
Pros : we see many types of tools and get to use some of them in the programming assignments. I feel like I now have a general knowledge of the field. I particularly liked the aspects of scaling and deploying models in production.
Cons : This honestly feels more like a rough draft than a finished and polished course. I would have liked a consolidated overview of all these tools, their pros and cons, etc. Some tools and techniques were explained in literaly 15 min(!) and in some cases simply walked through a tutorial from the tool's website (!!). A programming assignment was broken through not being updated for more recent spark versions. Some videos mentioned a non-existent programming assignment (I assume they were reused from an internal IBM training session), etc. The comparison with say Andrew Ng's course on ML is cruel.
By Appan P•
Jun 07, 2020
Even though this course covers quite a bit of breath - in terms of implementation frameworks, there is scope of improving the presentation material. It will help a lot if the neural network models and the data transformations are explained using pictures.
Also, the one of the videos in the sequence of videos on LSTM for time-series forecasting (week3) talks about comparing performance of MSE and MAE but I could not find any such video on performance comparison.
Also, the assignments are quite simple and wish they had more steps for the student to "fill-up".
There is not much info on deploying the model and online evaluation of its performance. At least one video on how to do it in IBM data cloud will be helpful.
By Jakob S•
Mar 26, 2020
The course covers some very interesting and important concepts, however on a very low level. The reason for this might simply be the lack of time; one cannot properly cover methods for AI image processing, NLP, etc. in such limited space. I also had mixed feelings about the exercises: It is very nice to see applications of the tools discussed in the lectures, but unfortunately the exercises are so simple that they can be easily finished without really understanding the code.
By Manas S•
Jun 19, 2020
The course instructors are very experienced and knowledgeable but the teaching part has not been done very well. The assignments were not up to the mark, and an attempt to included too many topics in a very concise format was made. Some topics like Feed-forward NN in Keras were covered very well but most other things were a disappointment.
By Jose L M G•
Apr 01, 2019
Lo hago, el curso es muy bueno en cuanto al uso de la plataforma watson, pero falla en explicar los fundamentos principales con animaciones, ejemplo, el curso de pytorch de udacity enseña eso muy bien. En lo demas esta bien, pero al no contar con elementos visuales de ayuda en laclase de LSTM se hace tediosa.
By Jeet D•
May 12, 2018
The course is very resource heavy, i.e. it has great intuitive resources, but the learning experience was very poor. Some of the instructors were very sparse with the material contents, some just brushed over the contents without much explanation and.
The quality of the course has to be improved.
By Julián M•
Jun 16, 2020
You can learn several things from this course but you need to know Neural Networks and Deep Learning in advance. The content looks a bit disorganized but still pretty useful for day to day Deep learning implementations. Really cool the System ML integration with Keras.
By Daniel P•
Jul 10, 2018
Too much focus on IBM platform, good overview on Keras/SystemML/DL4J though, some presentations could have been better prepared and implemented. Overall an average Coursera course and not a particularly great experience to work through the material.
By Eugene N•
May 22, 2020
Something happened to the free 1CPU 4GB python environment on IBM watson studio. It is unavailable and so I had to struggle with Skills Network Labs instead. Please can this be checked?
By Robert F•
Jul 04, 2020
Fairly okay course. Lectures were real hurried and high level. Had it not been for my Math and CS background I would not have gotten most of the material.
By Ceren A•
May 10, 2020
Several lectures were superficial. I feel like I need to put a lot more time on my on to understand how to build a proper neural network model.