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Learner Reviews & Feedback for Scalable Machine Learning on Big Data using Apache Spark by IBM

3.8
stars
1,037 ratings
270 reviews

About the Course

This course will empower you with the skills to scale data science and machine learning (ML) tasks on Big Data sets using Apache Spark. Most real world machine learning work involves very large data sets that go beyond the CPU, memory and storage limitations of a single computer. Apache Spark is an open source framework that leverages cluster computing and distributed storage to process extremely large data sets in an efficient and cost effective manner. Therefore an applied knowledge of working with Apache Spark is a great asset and potential differentiator for a Machine Learning engineer. After completing this course, you will be able to: - gain a practical understanding of Apache Spark, and apply it to solve machine learning problems involving both small and big data - understand how parallel code is written, capable of running on thousands of CPUs. - make use of large scale compute clusters to apply machine learning algorithms on Petabytes of data using Apache SparkML Pipelines. - eliminate out-of-memory errors generated by traditional machine learning frameworks when data doesn’t fit in a computer's main memory - test thousands of different ML models in parallel to find the best performing one – a technique used by many successful Kagglers - (Optional) run SQL statements on very large data sets using Apache SparkSQL and the Apache Spark DataFrame API. Enrol now to learn the machine learning techniques for working with Big Data that have been successfully applied by companies like Alibaba, Apple, Amazon, Baidu, eBay, IBM, NASA, Samsung, SAP, TripAdvisor, Yahoo!, Zalando and many others. NOTE: You will practice running machine learning tasks hands-on on an Apache Spark cluster provided by IBM at no charge during the course which you can continue to use afterwards. Prerequisites: - basic python programming - basic machine learning (optional introduction videos are provided in this course as well) - basic SQL skills for optional content The following courses are recommended before taking this class (unless you already have the skills) https://www.coursera.org/learn/python-for-applied-data-science or similar https://www.coursera.org/learn/machine-learning-with-python or similar https://www.coursera.org/learn/sql-data-science for optional lectures...

Top reviews

AC
Mar 25, 2020

Excellent course! All the explanations are quite clear, a lot of good quality information provided from amazing teacher. Additionally, response times for any question is very fast.

CL
Dec 11, 2019

Really really REALLY enjoyed this course! The instructor does a masterful job of going from simple examples and building up complexity in a very logical and thorough way.

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26 - 50 of 269 Reviews for Scalable Machine Learning on Big Data using Apache Spark

By Yuting K

Oct 3, 2019

The quality of the videos could be better

By andrei-klepikov@yandex.ru

Jul 8, 2020

Too high-level, mismatch between code and Watson setup Video vs working notebooks, teacher does not explain basic building blocks re RDD and DF what is the difference, when each of them should be used, complicated subjects have videos by 3-5 minutes, absolutely simple exercises. What is the basic difference with sckitlearn and how different work should be organized. NO any supporting materials, some code is not working, errors in videos with clues "don't do this"... Not serious approach for building this course. Sorry

By Adrian I

Sep 22, 2020

I don't feel I've learnt much in this course and I certainly can't recommend it. The videos are of poor quality and the selection of examples is bad (use real use cases instead of explaining basic statistics). The quizzes are way too easy and require no problem solving at all. This course needs being redesigned from scratch.

By Carolin A S

Jul 29, 2020

I have done some great Coursera courses before but I am disappointed by that one. The course covers some superficial topics without really explaining the basic concepts of Apache spark & big data. I had to do extra research just to understand what I was currently doing. I am sorry to say but I cannot recommend it. You get a lot of "Don't worry, you do not have to understand that coding as you will not be asked about it." But I really want to understand the coding. Looking back I do not feel comfortable in using Spark now and I guess there are more suitable courses for learning that in more detail.

By Ryan B

Jul 23, 2020

This was the worst course that I have seen on Coursera so far. The language barrier of the instructor was difficult at best. Some of the questions on the pop quizzes you would need to guess at bc he hadn't taught it yet. The end of week quizzes themselves were not that instructive. The only reason I finished this course was for the certificate. Someone needs to redo this course.

By Yuanlong S

Nov 15, 2020

good contents and hard to follow actually if lab answers not shown directly. I have the feeling that the instructor knows a lot and it would be great if he can express that in a easily understnadable manner. Anyway its a hard job itself.Btw, some of the statistical part are consistent with scileanrn but executed in differnet methods. Modeling and testing part the underlying idea is the same. Pipeline is so powerful hope it is useful in the future. Thanks to the Instructor, and may learn his other lessons as well. I am shocked when seeing the PCA part which is so impressive, and the star ship of invader! Big likes! Cheers!

By Vedant B

May 15, 2020

just awsome and very very informative ...specially the whole process was done on the spachespark environment on the IBM-watson studio where whole processing is take placd on the working-nodes of the apacheSpark cluster under the Apache driver manager parallely, and most prefereble dataset format is used here is '*.parquet'(HDFS)

all is really essential to become datascientist, in the last thanks to instructor

By Edward J

Sep 29, 2020

Loved it. I've already done the Advanced Data Science specialisation but I've found this course really useful. It is great to have new notebooks and a range of evaluators and classifiers being shown. I've already picked up things that I would want to add to my final project in the previous specialisation. Thanks again, Romeo. I hope you'll continue to make new courses as I enjoy your teaching style.

By Fasiuzzaman M

Oct 23, 2020

excelent teacher and he has a nice way of building up the concepts in small, understandable steps. The best part I liked is that he explains the concept of Pipeline and uses it in all the following alogorithms thereby repeating the idea of pipeline everytime. This helped me personally because I learn with repeatation. Thank you.

By Tanmaya C

Aug 28, 2020

This is really an awesome course, I love the content of this course very much as it is very informative about the core work happen in Big Data.

I learned so much from this course like what is Big Data, how we deal with it, how to use Apache Spark & Spark ML with Pipelines.

Overall it's a good course to start learning Big Data.

By charlie b

Jun 8, 2020

Romeo explains these topics perfectly. If you take this class along with maybe one or two other applied machine learning classes I am sure you will feel very confident with the material. My only piece of advice would be to always follow along in your own notebooks and question what every.single.line does

By Afeef A

Apr 16, 2020

One of The Best Course I seen that combine Machine Learning with Apache Spark with awesome tutorial along with using IBM Watson studio which really help me to complete my course with one of the best tool along with the documentations. And really help any problem what i face so far using this course.

By Wei J ( T

Jan 29, 2020

I should not comment the way how this lecture has been carried out... HOWEVER, it does bring actual tooling skills and makes it interesting to use those instruments for real life situation. Highly recommended. Make your model maybe can be your crystal ball.

By A A A

Jul 6, 2020

Romeo Kienzler! Thank you so much! This course showed the complexity of parallel computing and introduced Functional Programming in a very simplified and understandable way. The way statistics was explained, was something I couldn't even get from college.

By Karim V

Feb 11, 2020

Learned several new skills. Instructor did an excellent job of explaining the concepts starting with the notion of big data and showing us how to run ML algorithms on apache spark and use of pipelines.

By ANGEL G C

Mar 26, 2020

Excellent course! All the explanations are quite clear, a lot of good quality information provided from amazing teacher. Additionally, response times for any question is very fast.

By charles l

Dec 12, 2019

Really really REALLY enjoyed this course! The instructor does a masterful job of going from simple examples and building up complexity in a very logical and thorough way.

By Mohd N K

May 1, 2020

I like the example given and step by step tutorial given. The explanation of why things are the way they are designed certainly helped me understand the concept. Kudos.

By Arshdeep S

May 30, 2020

It was a great experience , learned a lot about Apache Spark, Programming assignments helped a lot in grasping the concepts

By Adaobi A

Jun 17, 2020

The videos were not so awesome, but the curse was superb overall. It really addressed the intricacies of large data.

By Moez B

Dec 30, 2019

Good course. Beginner level, it starts slow and gets better in weeks 3 and 4. Instructor is very helpful.

By Rogerio A

Jun 24, 2020

Great course. The instructor is simply amazing and so knowlegeable. I definitely recommend this course.

By RATHEESHWARAA K

May 6, 2020

This course is structured very well and the assignments and notebook given are really great resource.

By Lee Y Y

Feb 9, 2020

Easy to follow and clear. May introduce more about Apache Spark usage in different fields/industries

By Shrinivas S

Jan 31, 2020

Great Hands-On activity, good pace so you are not lost and complete the learning objectives.