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Advanced Machine Learning and Signal Processing

Advanced Machine Learning and Signal Processing

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8.5/10 (Our Score)
Product is rated as #126 in category Machine Learning

>>> 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 …

Instructor Details

Romeo Kienzler holds a M. Sc. (ETH) in Information Systems, Bioinformatics & Applied Statistics (Swiss Federal Institute of Technology). He has nearly two decades of experience in Software Enineering, Database Administration and Information Integration. Since 2012 he works as a Data Scientist for IBM. He published several works in the field with international publishers and on conferences. His current research focus is on massive parallel data processing architectures. Romeo also contributes to various open source projects.

Specification: Advanced Machine Learning and Signal Processing

Duration

15 hours

Year

2018

Level

Expert

Certificate

Yes

Quizzes

Yes

51 reviews for Advanced Machine Learning and Signal Processing

3.9 out of 5
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  1. Euripedes B d C N

    O Curso e otimo e apresenta muitos conceitos de Machine Learning e Processamento de sinais, mas faco uma ressalva, pois como o proprio nome diz e Avancado e o candidato precisa ter uma boa base de programacao, particularmente precisei pesquisar bastante sobre Apache Spark e Systemml pois minha formacao nao e de TI.

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  2. FREDDY Y

    best course to gross, even for beginer

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  3. Aditya S K

    Great learning!!!

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  4. Michael S

    thanks a lot to my motivated, sympathic and well prepared teachers

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  5. Varadharajan R

    I enjoyed this course thoroughly

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  6. Michael B

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

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  7. Oghenekaro J O

    Great Course. You’ll learn a lot about the mathematics of some key algorithms.

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  8. Mario E R T

    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.

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  9. Ted H

    The Signal Processing was eye opening as a way to extract data from sampled data.

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  10. Sukh S S

    The explanation of some of the black box tools like PCA, Covariance, and Fourier Transformation is amazing and very clear and easy to understand.

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  11. Prashant B

    The spark usage is very limited. Assignments could be more challenging.

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  12. Srivatsan R

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

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  13. Sheen D

    Seriously, the guest instructor was not clear at explaining anything. I have no idea what he’s saying… even while reading subtitles, it says inaudible… from time to time.

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  14. 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.

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  15. Amy P

    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.

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  16. Julien P

    Very happy about the content and the emphasis on applications!

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  17. Anastasiia S

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

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  18. Bjorn ‘ 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.

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  19. Felipe M M

    Videos are old. It feels like he had a bunch of material and put them together to create this course. For example: There are assignments that they give you the answer because the questions are not supposed to be there. He doesnt teach, instead, he reads a script. The assignments are not challenging and you dont feel like you learned. Horrible and painful.

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  20. Tushant T

    Too difficult

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  21. Markus W

    well explained, programming assignments are worthless.

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  22. 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

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  23. Pratyush A

    IBM Watson studio can be made more user friendly.

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  24. PV R K

    very informative

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  25. yash k

    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

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  26. Debakanta G

    Awesome experience of learning this coursera

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  27. Saman S

    that’s wonderful

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  28. Eleni K

    Quite different from the previous course! Much better, with more thorough explanations and hands on experience.

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  29. N B

    nice

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  30. Alexander B

    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.

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  31. Prithvi S

    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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  32. Bikash R

    Great

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  33. BAUDRY S

    Some spelling errors here and there

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  34. Sauraj C

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

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  35. Madan K

    Excellent course

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  36. Abdelfettah H

    it was really helpful, thank you so much.

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  37. Jan K

    Great course for beginners who want become advanced users in signal processing and machine learning. Thanks a lot for great examples and letting me know what I should learn in next steps.

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  38. Ankit M

    Good

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  39. Carlos F C d S e S

    Great course!

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  40. Petch C

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

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  41. Nafih A A

    A bit tough for a beginner but nonetheless very informative

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  42. 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.

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  43. Giovani F M

    Great course. I really enjoyed the approach about FFT and Wavelet.

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  44. Armen M

    Terrible, I am so sorry. Some parts of code I can’t run in my IBM watson studio because there are not exist python 2 ,

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  45. Salvatore S

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

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  46. Jeffrey G D

    Great concepts, but light on application.

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  47. Albert S

    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.

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  48. Jeremie B

    Good.

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  49. Jan B R

    It was a really nice course to learn the way to implement the most used ML algorithms with an easily scalable method

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  50. David A

    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!

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  51. Sriram R

    Well defined course with good concepts

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    Advanced Machine Learning and Signal Processing
    Advanced Machine Learning and Signal Processing

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