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Advanced Machine Learning and Signal Processing に戻る

IBM による Advanced Machine Learning and Signal Processing の受講者のレビューおよびフィードバック



>>> 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



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.


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.


Advanced Machine Learning and Signal Processing: 151 - 175 / 206 レビュー

by Ahin B


I have earned good knowledge on Machine learning along with python programming.

by Kuldeep S S


This Course is very good but programming explaination is not good.

by John M


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

by Pratyush A 1


IBM Watson studio can be made more user friendly.

by Camilo A S B


Good, I would like more programming explanation

by Estananto


Great videos help me to understand the topics.

by Swarupa D


it's very helpful...Thank u Sir for guiding me

by Krishna K N


Programming exercises could be more difficult.

by Pragati A


Both of the instructors were really amazing.

by Jeffrey G D


Great concepts, but light on application.



Some spelling errors here and there

by Rich E


Great explanations and examples

by 俊鴻 林


Thank courser and teachers

by Aditya K


Great learning!!!

by Megha S k


Very Good Course

by Chris E


A good summary of machine learning, but way too quick. Only skims the surface and I doubt anyone could come away from this course with a good understanding of the material. You will know how to write the required code in Apache Spark but fundamentals are limited, so developing and iterating your models outside of the code templates will be difficult. Likely to have a lot of people creating models that they have no idea about how they actually work, or even if they do work.

by Filip G


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 Stefan T


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.

by Jeramie G


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 Roger S P M


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.

by Sonja T


Good material. Hard to understand the instructors' English. Not professionally presented. Assignments are too easy, and we didn't get good, meaningful practice. Quizzes often address information that either the instructor failed to present well, if at all, or made mistakes on.

by Mohsen F


It is supposed to be an advanced course but there is almost no advanced topic in this course and it is just a shallow overview of machine learning with the Pyspark. SystemML explanation was very vague and incomplete.

by Björn ' H


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.

by Michael P C


Excellent brief math lectures by Manchev. The course materials do MOST of the programming for you and so you only get a light exposure to the Apache Spark API -- insufficient to develop real proficiency.

by Greg R


Overall very useful material covered however I was disappointed that some key concepts such as Baynesian inference and PCA were not well explained. I supplemented most of that material from Youtube.