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Learner Reviews & Feedback for Advanced Machine Learning and Signal Processing by IBM

999 ratings
169 reviews

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, Advanced Machine Learning and Signal Processing, is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines. We’ll learn about the fundamentals of Linear Algebra to understand how machine learning modes work. Then we introduce the most popular Machine Learning Frameworks for python Scikit-Learn and SparkML. SparkML is making up the greatest portion of this course since scalability is key to address performance bottlenecks. We learn how to tune the models in parallel by evaluating hundreds of different parameter-combinations in parallel. We’ll continuously use a real-life example from IoT (Internet of Things), for exemplifying the different algorithms. For passing the course you are even required to create your own vibration sensor data using the accelerometer sensors in your smartphone. So you are actually working on a self-created, real dataset throughout the course. 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

Top reviews


Sep 08, 2018

A career changer course, thanks the hand-ons which is second to none, i have gained experience which on other online course can produce, thanks to IBM for this course which timely and excellent.


May 14, 2020

Good one! I liked the wavelet transform part. It was nice to visualize everything. However coding assignments are easy, almost all the codes are written, please insert some more coding part.

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76 - 100 of 168 Reviews for Advanced Machine Learning and Signal Processing

By Stanislaw K

Jun 26, 2018

Outstanding lectors!

By Marvin L

Apr 10, 2020

it was educational

By Mukul K M

Jun 13, 2020

excellent course

By Madan K

Dec 11, 2019

Excellent course

By Saman S

Oct 26, 2019

that's wonderful

By Dr P R K

Oct 18, 2019

very informative

By Carlos F C d S e S

Dec 25, 2019

Great course!

By Warren P

May 09, 2020

Great class!

By Hadhrami A G

May 06, 2020

Very Good


Jun 22, 2020

too good

By Jérémie B

Feb 03, 2020


By Bikash R

Nov 21, 2019


By Ankit M

Dec 17, 2019


By Nyam-Ochir B

Nov 05, 2019


By Avijit P

Jul 08, 2020

The difficulty level of the course is as it states, intermediate.

Both the instructors are quite good at explaining things and also provide a little insight as to why they're choosing to do something at any given moment.

There is this one lecture though from a guest faculty that just plain reads out what's written in the presentation slides.

Although they try to explain every short thing, it might go over one's head or require repetition if the reader is 2 or 3 viewings with the mathematical concepts behind the algorithms previously. But the course still felt pretty self-contained to me,

Still, it's an overall balanced course that can't be completed unless one understands what the code is doing. Great for getting insights on and developing data science intuition.

By Scott B

May 04, 2020

The information in the videos is excellent. I am actually very please by how succinct and clear the topics had been covered. My reason for giving 4 stars is because the programming assignments do not really help crystallize the new material. They may include a fraction of the concepts that are covered. It would be nice if the assignments involve stuff like the inclusion of param grids, comparing different ML algorithms, implementing PCA, etc. Also would be nice if there had been a review of the Fourier Transform material using SparkML.

By Alexander B

Nov 07, 2019

Overall a decent course. The lecturers could go into more depth with some of the topics they covered to allow the learners to really grasp the concepts. I felt all of the assignments were too simple, possibly allowing you to pass even if you don't completely understand the material. More depth in the lectures and challenging assignments would leave me completely satisfied.

By Taresh B

Jul 05, 2020

I like the course but I feel that it really needs more depth. It feels like most topics have been just skimmed through and not explained very well. The IBM tag is something that attracts you but if you wanna delve into the details, this course will tell you what to learn, and then you'll have to go on youtube and look for resources.

By Rishiraj A

Jul 08, 2020

I liked the course.

I like Week 4 of Advanced ML course. It is very fulfilling.

But, I think the portion of large data handling using parquet and spark is still missing in both the course (Scalable DS and Advance ML). There should be a session where is taught how to create parquet files and how to store them in object storage.

By Euripedes B d C N

May 20, 2019

O Curso é ótimo e apresenta muitos conceitos de Machine Learning e Processamento de sinais, mas faço uma ressalva, pois como o próprio nome diz é Avançado e o candidato precisa ter uma boa base de programação, particularmente precisei pesquisar bastante sobre Apache Spark e Systemml pois minha formação não é de TI.

By Florian B

Jun 26, 2020

Of course, the course requires that you are somewhat familiar with mathematical aspects of higher analysis!


It shows you the application of this knowledge to real world cases (especially week 4). I found the programming tasks and cases ideal for viewing the different methods.

By Joseph B J

May 17, 2020

The course was very intuitive. I have given 1 star less due to the 4th week's assignment. I feel it would have been more useful if there was an assignment where we could use SparkML instead of SystemML as it is not taught well enough in this course.

By Albert S

Jan 16, 2020

Assignments were a bit too easy. I didn't really have to understand 90% of the lectures to complete the assignment. Most changes were related to spark.sql knowledge and how to instantiate classifiers and such.

By David A

Feb 17, 2020

Overall good course; very interesting concepts given in the lectures. I only wish the programming assignments were a little more interactive and deeper than "fill in the blank." Great stuff though thank you!

By Amy P

Sep 07, 2019

Very interesting concepts and more math than other courses, which was nice. The audio quality of guest lecturers needs to be improved, but I appreciated the video content and hands-on examples.