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

3.8
stars
1,126 ratings
293 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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76 - 100 of 294 Reviews for Scalable Machine Learning on Big Data using Apache Spark

By Nguyen T T

Jun 9, 2020

Handful material, great course!!!

By Edson J M

Aug 4, 2020

Perfect course to learning Spark

By Pratik P

Jun 14, 2020

Great Course Highly Recommended

By Michel G E H

Mar 23, 2020

Amazing course! Thank you!

By Vaibhav Y T

Nov 9, 2020

Excellent Course!

By Krishna H

Apr 26, 2020

Very good course!

By Ever A B V

Mar 25, 2020

excellent course

By Erickson D M d F

Sep 20, 2020

Excelente Curso

By SAMIR B

May 9, 2020

detailed course

By Julien V

Apr 28, 2020

Great course !

By Vivek C

Jun 14, 2020

great trainer

By Harsh S

Oct 17, 2020

great course

By Aditya M P

Dec 1, 2020

Good Course

By Manjot S D

Jun 17, 2020

Masterpiece

By PARITOSH P

Jan 8, 2020

Good course

By Yassine E

Jan 10, 2020

Awesome :)

By Dr.Lakshmi D

Jul 8, 2020

Excellent

By Krish g

May 30, 2020

fabulous

By shaik m y

May 11, 2020

Good

By ashish k

May 3, 2020

good

By Aaron C

May 11, 2020

TLDR for those who don't want to read through all of that, the course gives a shallow entry into the data engineering part of machine learning. I wished they would make the course more challenging, so that we would learn more.

For people considering the IBM AI engineering specialization and this course, I would say that it is a very good introduction. For those looking for a more in-depth approach to ML and DL, then this course isn't going to hit those areas. Regarding this course specifically, they did a good job explaining the concepts well. I would have preferred if they made the course proejct a lot less hand holding. They essentially give you the jupyter notebook with all the ETL procedures done, and you change like 4 variables, which isn't really intellectually stimulating or challenging. I understand that the course is meant to be an introduction, but I think asking us to do the ETL by ourselves with less rail guards would teach the students a lot more. Like I would say I learned more about Apache Spark and functional programming from the 2nd module quiz than the course project, because the quiz had us writing the code ourselves, and I had to learn and debug functions on my own.

By Simon P

Sep 26, 2020

I can't fault Romeo for his enthusiasm and engagement in the forum, and nor do I think his accent is a problem. I can say I learned something from this course, but there are a few negatives

-- Some parts appear unprofessional. This includes the initial videos filmed in the car, the prompts stating that parts are out of date, and the on-the-fly coding in the week 3 and 4 videos

-- The course is initially jargon heavy, but it is pitched at quite a low level otherwise. There is a lot of hand-holding, for the final project you make two alterations to the code already supplied and then copy and paste the results. It would benefit from a review of the didactics.

-- I would have loved to have had more opportunity to play with the data. Why not a tutorial on using SQL or data cleaning? Why not more on the application of the ML tools? There's a definite feeling of being in a sandpit and not being allowed out.

That said, I now have experience with ApacheSpark and I understand how to use it to implement some ML methods, which is good.

By Alpay S D

Apr 13, 2020

The content that is taught was actually satisfying, however, it is obvious most parts of the videos were outdated either due to the fact that they are for another course or they were simply not organized from the beginning. In addition, it would have been awesome If the instructor explained the codes more. I feel that I have learnt the basic idea but I need further self-study to make sense of everything we have covered in terms of the coding.

By Pamela W

Apr 15, 2020

I enjoyed this class. I worked with Spark a few years ago, but wasn't aware of Pipelines and Parquet. The incorporation of these concepts into the course was useful. The instructor is engaging, but speaks quickly sometimes and there are some translation challenges with his accent. I found myself reading some of the material because i had trouble understanding what he was saying.

By Emmanuel H

Jun 22, 2020

I would like to thank Romeo for teaching me. I apologize to rate the course at 3/5. I did like the course in general but I missed the practice of it. The methodology process did not help me to learn the practice. I scored better in most quizes on the first attempting while I could not guess how the code are written. I wish I did learn to interpret or rewriting the code

Regards