The content is for new comer of tf.keras OK.

When you have been in this area for a long time but still want to finish the whole specilization, pls go ahead and finish the final exam directly.

The week 2 of describing the back propagation is pretty nice, not too much detail but somehow it is using an example which is even clear at some points comparing to Prof.Ng 's course, however, wont let them competet each other

The course materials need to be updated to clearly show how to get to the labs. The video talks of one way but the real method is different. Although one is supposed to use the IBM Labs the staff gives direction to use google colabs. I downloaded the files to local machine and discovered the dependencies by accident.

One should not expect to learn much about Keras here. It is a basic introduction to DL and NN.

A very light introduction into training Neural Networks with Keras. Content is of good quality, but there is not enough of it to qualify as a course. Some weeks contain ~20 min worth of videos and a quiz. I bet all the material could have been condensed into just 1 week of video lectures and a final project week.

Final project is good, but it would be way better begin auto-graded instead of peer-graded.

A good course overall, with reasonably good explanations and step-by-step labs. However, the course did not really cover Recurrent Neural networks and Auto Encoders properly: the theory part was barely an overview and there were no code examples or labs related to them. It is a bit disappointing to see them in the syllabus but not covered in the course.

The course content is really good, because it explains a lot about the real background tech. Loved that one, also the code examples. BUT: the final exam was pretty all over the place and a big leap from what was in the course examples and notebook. Probably that should be reworked.

This course is too shallow in terms of content and too light in terms of workload, it can only serve as a stepping stone towards a more advanced course. It does accomplish its stated goal of offering an introduction to many Deep Learning concepts and Keras, but nothing beyond that.

The course content is very brief not much for getting a better understanding of topics. It can be a good starting course for someone but if you are interested in getting details of topics I recommend taking the courses of deeplearning.ai

+ Learnt a few things from the course.

+ The first lab about building a neural net from scratch was good.

- Passed the whole thing in just a few hours with no prior knowledge of Neural Networks or Keras.

- Short lectures.

- Very easy multiple choice questions.

- No presenter overlay on lecture videos.

- Overly prescriptive labs.

- Awkward and unnecessary dependency on Jupyter Notebook.

- Some poorly specified questions for labs.

Too basic and simple, especially for the different popular models. Not as good as I expected.

a bit outdated

Very Basic

Learning content was good, but making assignments was a nigthmare, I could not set up an IBM Cloud account, becasue they could not verify my payment card, when i asked them to help me, they just responded "We have reviewed your account/transaction and will not be able to offer services. No further information will be disclosed regarding this matter. Any card authorizations will reverse within 24-72 hours depending on the issuing bank.". They ghosted me completely and did not want to help. I do not recommend. It's no wonder that with this kind of customer attitude IBM is far behind the competition today.

One of my tasks is blocked by the team and I requested them to unblock it but no one has replied yet. It's the worst management. I have one day only to finish this course and get a certificate through my institutional email id because I am leaving the current institute on Monday. So i will be not able to complete the full course after this.

I want to continue my course and i have deadline until 25th of Nov. It is saying the page is under maintenance. Will you pay me that If I miss the deadline because of this meaintenance?

PLEASE CHANGE THE INSRUCTOR,WE NEED MORE DETAILS DISCUSSION

so bad

j

I really like this course as it has only provided me with the tools that I need to understand neural networks without overhelming myself with abstract mathematics or theories. It is indeed good to be equipped with foundational theories and mathematics, but they do not build much intuition without direct practice. I believe that theories can be learned along the process rather than being stagnant because you cannot grasp them initially. With this course, I have become proactive because this is more concept-based and the mathematics has a good visualization to it. I like the way it is designed and how the final requirement aids you while allowing flexibility.

This course is highly recommended to those who have a background in Python programming, and interested in the basics of neural networks without the exhaustive mathematics.

This was a good course and well paced. But I have a comment about the final project. It was not clear to me if the same model was being re-trained and improved upon in 50 trials - or if the idea was to do 50 trials to capture just how good a model it is, using different splits of the data. Since we were asked to find the mean and sigma of 50 trials - I assumed those trials would be independent and each one performed with a fresh model - otherwise it is odd to find a mean and sigma of a system that is converging to a final result. In that case it's only the final mean and sigma of the final trial that matters. So I think some clarity would help there - without giving it all away with regard to how to do the project.

Everything depends on AI & ML now. Before enrolling in Coursera’s IBM AI Engineering Professional Certificate Course, I had zero knowledge about Neural Networks & Deep learning. After completing the course, I am able to use these applications properly. It proved to be a total career game-changer.

Coursera has proven to be a wonderful experience. I have taken classes from other organizations, but there’s no comparison to Coursera.

Highly relevant examples were given which made me get a clear idea of the concepts explained. Deeply appreciate Coursera & IBM for designing this course very well.

Kudos to Instructor Alex Aklson, Ph.D., Data Scientist for providing such a wonderful learning Journey.

This course offers a thorough introduction to deep learning and neural networks with a focus on practical application using Keras. It is well-suited for anyone looking to get started with deep learning or deepen their understanding of neural networks. The combination of clear instruction, hands-on practice, and real-world examples makes it an invaluable learning resource. I highly recommend this course to anyone interested in deep learning and neural networks. Whether you are a beginner or have some prior experience, this course will provide you with the knowledge and skills necessary to excel in the field of deep learning.

IBM's "Introduction to Deep Learning & Neural Networks with Keras" course is a game-changer for anyone stepping into the realm of deep learning. From start to finish, it's a journey packed with clarity, hands-on practice, and real-world relevance. The course breaks down complex concepts into easier and digestible parts, making it perfect for beginners while still engaging for those with some background. What sets it apart is the practical approach using Keras, a user-friendly tool that simplifies deep learning implementation. I learnt so much from the final project, which was fascinating implementing machine learning!

I loved the Introduction to Deep Learning & Neural Networks with Keras course! It was a great way to learn the basics of deep learning and how to use Keras, a popular and user-friendly framework for building neural networks. The course was well-structured, with clear and engaging lectures, quizzes, assignments and peer reviews. The instructor was very knowledgeable and helpful, and the practical elements of the course were very helpful. I learned a lot from this course and I highly recommend it to anyone who wants to start their journey in deep learning!

I found this course to be very beneficial. The explanation was consice and straight to the point without wasting any unnecessary time on explanations of concepts that a student couldn't readily put into practice. I found the labs to be equally as concise and to the point. It allowed me to understand fundamentals and build programs quickly. I would suggest this course to anyone wanting to get up to speed quickly regarding Deep Learning and Keras in particular

Best course yet of the IBM professional certification courses. Everything was clear and to the point. The final assignment lab was presented with clear instructions. I learned a lot and more importantly found a new favorite focus!

Although instructors never responded to questions I posted on the forum (usual), with a search was able to get clarity on details of the assignment. I enjoyed the lab.