It's a course about a lot of things: speech recognition, music generation, image captioning, machine translation, ecc.

It's highly recommended to study previous courses to fully understand the concepts.

There are some errors in the exercises because it's a new course.

Very good course: the lectures are clear and motivating, the applied exercises help to improve the understanding of the topics and its implementations, and is very nice that for each topic the teacher incentivizes to read the papers from which this ideas came from.

This course gives a very good introduction to exciting applications of Deep Learning,that too in a very short time span. It is worth the time and effort to learn a complex thing in such a lucid manner. The instructions in the programming assignment has helped a lot

Pellucid, succinct, and the final bomb of this specialization! Felt a little dazed sometimes during the course and some things didn't really make some sense, but after things do settle after a re-watch. This course is so good it is actually re-watch recommended. :P

E​xtremely helpful for those who are interested in NLP, rich content and easy-to-understand illustration on complication models and methologies. Would recommend to add more content introducing popular pre-trained model such as BERT and GPT 3 and their applications

As usual, an amazing course by Professor Andrew Ng. The course manages to convey the most important elements of such a critical field, teaching from papers which were published only a couple of years ago. For anyone who wants to work in AI/ML, this is a must-do.

This course helps me understand more about RNN and its variations, especially I learnt about the basic of Attention mechanism. What I enjoy the most in this course is its assignments, these are very practical and easy to understand. Thank you for reading these.

This course was quite amazing in understanding with top papers discussed how machine translation and word trigger detection is carried using RNN. Code assignment was the best to show detailed steps of building RNN with a lot of hints to keep you moving forward

Great Course! Thanks for Dr. Andrew Ng's and mentors' efforts for making this course excellent! However, as deep learning - AI quickly marches, I think more and more courses from Dr. Ng's group will be expected by all of us! Hope to see your new courses again!

In my opinion, this was the toughest course of this entire specialization. It was like a lot of detail squeezed into a few videos. I had to rewatch a lot of times to actually grasp the concepts. But thank you, Andrew and team, for your motivation and efforts.

Gracias a Andrew y a todo el equipo de apoyo!! El curso es muy bueno!

Espero empezar pronto a aplicar estos conocimientos en la solución de problemas de nuestras comunidades y en mejorar las herramientas educativas de la Fundación MINCI con la que trabajo.

Good introduction to sequence models. Would be nice that the exercises weren't as guided, since it would be better to implement most things yourself rather than use so many predefined functions. However, I understand the necessary trade-off in terms of time.

One of the best Professors I ever came across. This Course is Precise and Clear. I am writing this today and will view is again when I achieve success in my life " This Specialization is the stepping stone towards my future "

Thank you, Professor Andrew Ng,

The course is another great addition to the specialization. Very well designed and delivered. A big thank you to the Professor Andrew Ng and his team as well as Coursera. It was a great experience and I am very pleased that I took the entire specialization.

A tough one. The notebook was very slow and and unstable.I like the original ML course's way of guiding us more. The suggestions on what should be done on every line make me lazy and I often don't focus hard enough on the intuition and math behind the code.

Great course! Andrew is great in explaining complex definitions with simple and understandable explanations. The course goes deep in multiple applications of Sequence Model for Time Series Data, and the programming exercises are challenging and rewarding.

The course detailed, informative and elaborate. The programming exercises are using libraries Tensorflow and Keras. A familiarity of these libraries is very helpful. It would be great if an introduction to the fundamentals was a part of the course itself.

As always Prof Ng explains complicated ideas in a very easy to understand step-by-step breakdown. Really an excellent course with some fascinating application examples you'll want to spent some time playing with yourself long after the course is finished.

This was one of the most interesting and well taught courses here. After this course, I was able to understand research papers in this area which were previously quite difficult and alien to me. I was also able to implement the models in them successfully

Learned a lot of new skills and faced really great challenge especially when using different framework, troubleshooting make me feel headache. But learning new framework is also exciting. Still have a long way to go. Thank you so much Andrew and the team!

Brilliant, the best introduction to sequence models I could hope for. Because the material goes through multiple levels of complexity, I revisit it on a regular basis, even after finishing the course, and every time I am able to gain additional knowledge.

This was an awesome sequence. I wanted to understand Deep Learning and the techniques and ideas that had advanced the state of the art beyond ordinary neural nets. I was particularly interested in Sequence Models which are of interest in my line of work.

Great course! It teaches the necessary to implement deep neural networks problems and give you practical advice. You can go deeper as you want in the material of this course, the programming assignments can be extended by going into the optional content.

So much gray area about sequence model was covered here! Broad topics covered with practical exercises make this course a must-have when dealing with sequence-related problems in deeplearning.

Thank you Andrew Ng and to the team for this wonderful course!

Thanks to DeepLearning.AI, I now have good grasp of Sequence Models and their techniques. I really hope that DeepLearning.AI team will create more amazing and helpful courses like this in the future. Best wishes to all of the members of DeepLearning.AI!