I learned many things from this course. However, I think in some points it could have been instructed much better. But all in all, it is a very worthy course for the price offered. Thanks a lot!
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
par Scott L•
This class had some interesting information, and some lectures provided additional insight into the world of AI and deep learning, but more often than not I found it to more be a showcase for the ibm platform(not a bad thing and possibly good for people already working in the field). So overall I would say this is just above average, I would give it a 3.5 if I could.
par Naveen M N S•
Very hands-on course. Enjoyed the width of problems that were solved. IBM cloud seems irresistible. Certain sections of the course are too fast. For such sections it will be better if the notebook links are provided in the video/description itself.
par Filip G•
Nice course with lots of practical examples. Course is delivered by multiple tutors with different styles and level of detail. Overall good introductory course into neural networks, scaling and deployment.
par Omkar G•
The content of the course gives an idea of several techniques of deep learning. But The concepts ain't explained completely here. Though assignments can be helpful for better understanding...
par Giovani F M•
I've learned a lot from this course. I've very much the Time Series Forecasting Section Explanation. The notebook is detailed and the concepts very well discussed.
par Dmitry B•
This course is packed with info on different deep learning techniques and libraries. Not all of them can be found in exercises though.
par Muhammad S u•
Since they are updating the module, still LSTM and CNN were taught extremely well. I am eagerly waiting for the updated materials :)
par Saurabh W•
One of the great course from IBM Watson .Really one should take this one if intrested in Deep Learning.
par Thomas B•
This is a good course with good introductory material that covers a broad range of topics.
par Chandan C•
Exercises let me explore the topic further which was very helpful for my learning
par Mrutyunjaya S Y•
This course gives you a overall concepts of AI with DeepLearning ...Nice course
par Sourastra N•
The course needs to allow the students to build their own model.
par Dmitry G•
Concise intro to much needed big data machine learning solutions
par Victor d O•
I think we need in this module more pratical assignments.
par PRASHANT K R•
very nice course it gives more insight to deep learning.
par Jair M•
Some videos are missing, but anyway is a great course
par Amalka W•
Course covers scalerble deep learning concepts
par Andrey O•
Part with DeepLearning4J is not very good...
par Deleted A•
Really Helpful course for AI Enthusiasts
par Mobassir H•
pytorch instructor was the best <3
par Valerio N•
Very Complete course.
par Aarti Y•
It was nice
par Tobias H•
par Pierre-Matthieu P•
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.
par Appan P•
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.