Applied AI with DeepLearning

As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability.If you choose to take this specialization and earn th

Created by: Romeo Kienzler

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Quality Score

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Overall Score : 80 / 100

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Course Description

>>> 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 <<

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Instructor Details

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Romeo Kienzler holds a M. Sc. (ETH) in Information Systems, informatics & Applied Statistics (Swiss Federal Institute of Technology). He has nearly two decades of experience in Software Enineering, Database Administration and Information Integration. Since 2012 he works as a Data Scientist for IBM. He published several works in the field with international publishers and on conferences. His current research focus is on massive parallel data processing architectures. Romeo also contributes to various open source projects.

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Reviews

4.0

82 total reviews

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By Felipe M M on 19-Sep-19

Videos are old. It feels like he had a bunch of material and put them together to create this course. For example: There are assignments that they give you the answer because the questions are not supposed to be there. He doesnt teach, instead, he reads a script. The assignments are not challenging and you dont feel like you learned. Horrible and painful.

By Francisco J G L on 2-Jul-19

Very bad course

By Chiara P M on 2-Jul-19

poor expalined. Too many things threw there without proper explanation. Poor exercise with the notebooks. Better less things with higher focus

By guoqiong s on 19-Sep-18

The video quality is very low, it is impossible to see the screen

By mathias s on 16-Mar-18

The instructions are missing a lot of things and repeating them self with some modifications, that changes some things that you have to do.There is also general problems with the IBM setup, when using the services, due to missing selection setup.

By Amin s on 31-Mar-19

even after getting financial aid i am not able to upload my submissions.

By Serdar M on 22-Mar-19

materials offered are not enough, and it is confusing.

By Csaba P O on 1-Oct-19

I liked the general idea of this course, but the actual material is not as good as it could be. There are lots of inaccuracies in the material (like annoying typos and not working code examples) which should be corrected before you sell this course on Coursera.I strongly suggest that you go through your material with someone who has pedagogy knowledge and who can assist you to improve the didactic aspects of your material.I did this course (and the whole specialization) for the practical examples as I feel rather confident with the theoretical aspects of machine learning, but I wanted to learn how to do these things in Spark environment. At the end of the day I have got what I wanted (more or less, as the NLP part was really lousy), but if I would not have strong experience with the field, I would have been surely lost. Honestly, I would have a hard time to recommend these courses for someone who wants to learn about machine learning and not about how to do machine learning with Keras, etc. And I am sorry to say that, because, again, I liked the team, the attitude, and the technical aspects of this course.

By Sheen D on 1-Sep-19

Again, the instructor speaks way too fast to explain anything. Even the subtitle cannot follow the instructor line by line. Frequent occurrence of inaudible words or sentence or wrong translations. When it comes to the code, never really understood what each line of codes is for...

By Leonardo I on 28-Aug-19

The course is delivered at a very high level of abstraction. If you are a beginner, I wouldn't recommend this course as the explanations provided are quite vague and not so good in many instances. Justifications for the use of quite a couple of algorithms/values are not provided thus leaving the learner with a lot of "Why's" One of the nice things about the course is that the instructor responds promptly to students' queries.

By Jorge A V on 5-Feb-19

Explanations are a bit rush. Would not be easy to follow if I would not have deep previous understanding on the Deeep learning topics.

By Daniel P on 10-Jul-18

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.