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

1,189 évaluations
218 avis

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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101 - 125 sur 215 Avis pour Advanced Machine Learning and Signal Processing

par engin C

22 août 2018

Well structured course.

par mahmut k

4 juil. 2018

Great course from IBM!

par Stanislaw K

26 juin 2018

Outstanding lectors!

par Soumyajit D

1 oct. 2020

Very good , awesome

par Marvin L

10 avr. 2020

it was educational

par Mukul K M

13 juin 2020

excellent course

par Madan T

10 déc. 2019

Excellent course

par Saman S

26 oct. 2019

that's wonderful

par RK

18 oct. 2019

very informative

par Yuliia H

18 juin 2021

G​reat course!

par Alexander L

8 mai 2021

Very cool job!


25 déc. 2019

Great course!

par Suhas J

20 sept. 2020

great course

par Warren P

9 mai 2020

Great class!

par Hadhrami A G

6 mai 2020

Very Good


22 juin 2020

too good

par Jeff D

24 janv. 2021


par Jérémie B

3 févr. 2020


par Bikash R

21 nov. 2019


par Ankit M

16 déc. 2019


par Nyam-Ochir B

5 nov. 2019


par Avijit P

8 juil. 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.

par Humberto D

21 juin 2021

T​he instructors of this course are very good about explaining the intuition and the code. However, I must admit that the treatment of the mathematical content was superficial; there was not enough time devoted to mathematical formulations of the problems and their solutions. In fact, it is such that one should already be familiar with the mathematics of data science in order to understand what goes on under the hood during the coding implementations. Otherwise, one does not get a sense for why the techniques that are used work the way they do.

par Scott B

4 mai 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.

par Alexander B

7 nov. 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.