Advanced Machine Learning and Signal Processing

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

( 69 Reviews )

Created by: Romeo Kienzler

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Overall Score : 82 / 100

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 <<

Time: 16h

Instructor Details

Romeo Kienzler

4.1 Rating
69 Reviews

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

4.1

69 total reviews

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By Ã¦ÂÂŽÃ¦Â™Â¨Ã¦Â›Â¦ on 16-Nov-19

Great course. Finally after learning Transformation methods like Fourier and Wavelet, I finally got to learn real life problem solving capabilities of them. Learned a lot!!!!!

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 Muhammad E on 8-May-19

Instructor english is very bad and the content is not clear especially the systemML section.I am still studying the course but I fairly understand the instructor english even the subtitle has too many misspelling.

Pretty bad.

By Sheen D on 1-Sep-19

Seriously, the guest instructor was not clear at explaining anything. I have no idea what he's saying... even while reading subtitles, it says inaudible... from time to time.

By Tushant T on 21-Sep-19

Too difficult

By Serdar M on 22-Mar-19

second star is just because I was able to finish the course

By Jukka A on 16-Feb-19

Course was hard to complete due to the version problems. Instructors should update material so that the course can be done with newest versions of programs.

By Jeramie G on 4-Sep-19

The information and examples presented in this course are helpful and pretty easy to follow. My only complaint is - and this is true for a lot of these online courses - the programming assignments are way too easy. I know this isn't a full-blown college level curriculum. I feel like I retain the material better when the assignments are more challenging.

By Filip G on 27-Sep-19

This course is second in the IBM specialization. It covers basic supervised and unsupervised ML models on a very high level with too little explanations. Especially around veryfing results and optimizing models. Metrics, crossvalidation and gridsearch are all explained on cca. 10 minutes! On top I can't figure out why did the authors put in a whole week on Fourier Transformation.. :S

By Markus W on 24-Sep-19