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Learner Reviews & Feedback for Applied AI with DeepLearning by IBM

4.4
stars
1,109 ratings

About the Course

>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. We’ll learn about the fundamentals of Linear Algebra and Neural Networks. Then we introduce the most popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML. Keras and TensorFlow are making up the greatest portion of this course. We learn about Anomaly Detection, Time Series Forecasting, Image Recognition and Natural Language Processing by building up models using Keras on real-life examples from IoT (Internet of Things), Financial Marked Data, Literature or Image Databases. Finally, we learn how to scale those artificial brains using Kubernetes, Apache Spark and GPUs. IMPORTANT: THIS COURSE ALONE IS NOT SUFFICIENT TO OBTAIN THE "IBM Watson IoT Certified Data Scientist certificate". You need to take three other courses where two of them are currently built. The Specialization will be ready late spring, early summer 2018 Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give your ideas for turbocharging successful creation and deployment of DeepLearning models. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this course will help serve as your guide. Prerequisites: Some coding skills are necessary. Preferably python, but any other programming language will do fine. Also some basic understanding of math (linear algebra) is a plus, but we will cover that part in the first week as well. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging....

Top reviews

SS

Oct 23, 2020

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!

RC

Apr 25, 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

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101 - 125 of 197 Reviews for Applied AI with DeepLearning

By Madan T

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Dec 11, 2019

Excellent Course

By RK

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Oct 18, 2019

excellent course

By Joseph A

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Nov 3, 2021

Good quality!

By Deleted A

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Jun 5, 2018

amazing course

By Sabeur M

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May 13, 2023

Great Course

By Vishal G

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May 7, 2020

Its awesome,

By Gustavo H M d C

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Nov 5, 2019

Very good!!!

By Freddy Y

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Jun 6, 2019

great course

By SRAVANKUMAR E

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Feb 2, 2020

good course

By Jeff D

•

Jan 31, 2021

Thanks

By Md. S I S

•

Aug 14, 2021

great

By SHIVANI Y

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Sep 24, 2019

ossum

By KVD S

•

Mar 28, 2020

good

By Waleed M S A A

•

Feb 23, 2019

good

By A.Basit M

•

May 8, 2018

nice

By Toni K

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Oct 1, 2020

This is very challenging, but interesting. The only disappointment was with the last notebook example on deploying a simple model. Apparently, IBM watson had a recent library change, and the sample code had not yet been updated. It was also difficult to find the documentation on the new library to see how to update the code. However, this was not an assignment but an example, so it was not graded. The change is less than a month old. I am sure that the example will be updated soon.

Other than that, this course is very exciting, fun, and challenging!!

By Joseph B J

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May 31, 2020

Once again, the assignment's were not challenging at all. I know that some topics being taught are difficult and giving tough assignments makes everything complicated. So from tough assignments you should go to medium and not extremely easy ones. A small example would be to provide time series data and then let us try to model it ourselves. Medium difficulty. Apart from that, I enjoyed the course. Gained a lot of knowledge. Thank You.

By Scott L

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Apr 11, 2020

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.

By Naveen M N S

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Feb 18, 2018

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.

By Filip G

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Oct 9, 2019

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.

By Omkar G

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May 31, 2020

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...

By Giovani F M

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Jan 23, 2020

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.

By Luis A

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Dec 9, 2020

An exercise with time series forecasting is would have been indispensable (but at least there is an example). However, the course as a whole is great.

By Dmitry B

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Jan 11, 2019

This course is packed with info on different deep learning techniques and libraries. Not all of them can be found in exercises though.

By Muhammad S u

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Mar 14, 2020

Since they are updating the module, still LSTM and CNN were taught extremely well. I am eagerly waiting for the updated materials :)