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Отзывы учащихся о курсе Advanced Machine Learning and Signal Processing от партнера IBM

4.5
звезд
Оценки: 572
Рецензии: 87

О курсе

>>> 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 ibm.biz/badging....

Лучшие рецензии

A

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.

PS

Nov 16, 2019

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!!!!!

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51–75 из 86 отзывов о курсе Advanced Machine Learning and Signal Processing

автор: 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.

автор: 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.

автор: yash k

Oct 21, 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

автор: Zexi Z

Jan 01, 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.

автор: Michael B

Jul 30, 2019

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

автор: Petch C

Dec 27, 2019

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

автор: Andrés

Feb 17, 2019

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

автор: Sauraj C

Nov 26, 2019

4 Star because course is not based on project it's good to learn the theory project is important

автор: Srivatsan R

Sep 01, 2019

Great Online Course. Videos involving IBM Watson studio can be explained in a better way.

автор: Chan H Y

Oct 03, 2018

This course covers many traditional approaches to machine learning and signal processing.

автор: Sameera P

Sep 16, 2018

I like what's taught in the course but the questions assignments are too simple.

автор: John M

Jan 14, 2019

Great course overall. A few small wrinkles that need fixing.

автор: Pratyush A

Oct 18, 2019

IBM Watson studio can be made more user friendly.

автор: Jeffrey G D

Jan 15, 2020

Great concepts, but light on application.

автор: BAUDRY S

Nov 23, 2019

Some spelling errors here and there

автор: 俊鴻 林

Dec 03, 2019

Thank courser and teachers

автор: Aditya S K

Jun 27, 2019

Great learning!!!

автор: Filip G

Sep 27, 2019

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

автор: Stefan T

Dec 31, 2019

I don't like giving negative reviews, but for the amount of money asked for the certification I would expect better quality of material (audio especially). I took many courses back in the day it was free to do and the quality of material was much much higher.

The course is well presented, but if you don't use IBM environment and their libraries, you will not be so happy to follow.

автор: Jeramie G

Sep 04, 2019

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.

автор: Roger S

Jan 30, 2019

This is the second in the Advanced certificate series. By this time you are starting to understand their teaching method. So it is a better experience than the first one. Also you are getting more experience with the studio, cloudant, and Node-RED - which is very helpful and rewarding.

автор: Björn ' H

Sep 19, 2019

The assignments are too easy, the level of coding required is not very challenging, it's just a fill-in-the blanks exercise, I don't know if I could actually do any of these things on my own with a new data set.

автор: Mario E R T

Aug 09, 2019

The learner needs to do more by his own. I think the course should follow up on the teaching style from the IBM specialization of Data Science. The teachers are good at replies.

автор: Anastasiia S

Sep 15, 2019

Not enough programming assignments and the ones in this course are too easy for the "advanced" course

автор: Salvatore S

Jan 12, 2020

The assignments are way too easy. Not very challenging for a course with 'advanced' in its title.