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Avis et commentaires pour d'étudiants pour Advanced Machine Learning and Signal Processing par Réseau de compétences IBM

1,190 évaluations

À propos du cours

>>> 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

Meilleurs avis


28 avr. 2020

I learned a bit in terms of signal processing and the theory behind that. That could have been a course by itself, but the addition of great machine learning material made it a wonderful experience.


7 sept. 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.

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126 - 150 sur 216 Avis pour Advanced Machine Learning and Signal Processing

par Taresh B

5 juil. 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.

par Rishiraj A

8 juil. 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.

par Euripedes B d C N

19 mai 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.

par Adrienn K

11 août 2022

Intermediate rather than advanced (hence 4 stars because I find the title misleading). Good course though; interesting and applicable teachings. Perfect pace and clear instructors. Assignements could have abeen a bit more difficult. The required time to complete is much less than adverstised though.

par Florian B

26 juin 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.

par Joseph B J

17 mai 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.

par Joe-Kai T

5 avr. 2021

Good Course. I certainly learned quite a bit. It gives a good overview about the concepts and tools of machine learning and signal processing. The programming asignments were perhaps a bit too easy for an advanced-level course.

par Albert S

16 janv. 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.

par David A

17 févr. 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!

par Amy P

7 sept. 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.

par yash k

21 oct. 2019

Amazing course with real life usecase. A bit more explaination would have helped as most of the content is based on the fact that the viewers are familiar with SparkML/ SystemML

par Jennifer K

23 mars 2021

This class taught some Spark data pipeline basics using signal data as examples. The lectures on Fourier and Wavelet Transform were very thorough. Appropriate for beginners.


11 mai 2020

Really good if you know a bit about Machine learning, it's not important to know this in DML, could focus on this in python with scikit but still thoery is very useful

par Lawrence K

1 avr. 2020

Definitely worth the time, with good practical examples and a ton of maths behind Fourier Transform analysis and applying machine learning pipelines to Apache Spark.


23 juil. 2020

romeo class was too good , his information are too short and catchy , i like this course due to him , i am eager for any other course which he would teach

par Zexi J Z

1 janv. 2019

fairly good. not perfectly organized but a little bit relax. good pace for workshop style training for some parts and enough details for some other parts.

par Eugene N

16 mai 2020

This was a good course but I don't know how signal processing will be useful for some people who aren't in the field of physics (signal processing)

par Harsh J

28 mai 2020

This course help me learn many new concepts but I would suggest some coding exercises in the course would much better for the better learning.

par M B

29 juil. 2019

Great course overall! Personally, however, I didn't think the digital signal processing portion was as useful as the first three weeks.

par MEZOUAR b n e

4 juin 2020

it was very interesting to attend this course ,it had both theory and practice parts and all what you need to use in the future

par Ceren A

11 avr. 2020

Great classes from Nikolai but not so much from Romeo! Huge difference in levels, presentation, learnings between the 2.

par Petch C

27 déc. 2019

Content of the course is good and easy to understand but I would be better to add more activity to the assignment.

par Anh-Quang N

7 juin 2020

It is an OK course to learn the basics of ML in and how to use the IBM infrastructure with SparkML for ML

par Andrés

17 févr. 2019

The theory is good but the excercies could be more complete and big to cover all the points in the theory

par Zaire A

24 nov. 2021

Great Course but the title should be changed. Signal Processing is only focused on in the final week