Chevron Left
返回到 Scalable Machine Learning on Big Data using Apache Spark

學生對 IBM 提供的 Scalable Machine Learning on Big Data using Apache Spark 的評價和反饋

1,222 個評分
310 條評論


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) or similar or similar for optional lectures...



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.


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.


151 - Scalable Machine Learning on Big Data using Apache Spark 的 175 個評論(共 312 個)

創建者 Hayagreev S


Good Course! Was able to understand the complex python involved! Nice examples.

創建者 Heetanshu R


The professor's English is just hard to understand but otherwise it is good!

創建者 HoangVan N


This course is very good for me but there is a video not watch in Week 3

創建者 Zijie


It would be perfect if the coding showing screen could be more clear.

創建者 Roberto M


Good course, but the instructor sometimes seems to be a little off.




創建者 Vijander S


the programming environment is complex it should be explained

創建者 Maurício C B


Precisa ser atualizado. Possui correções em alguns vídeos.

創建者 Ilham R


this is a complicated course especially for beginners

創建者 Víctor M F S


Quizas alguna propuesta de ejercicios menos guiados

創建者 fulvio c


The lines of code provided are extremely valuable.

創建者 Utkarsh B


There should be some more exercises for practice.

創建者 Devarshi G


Would've loved if more practice tests were given

創建者 Harshit K L


The Course can be made to cover some more basics

創建者 Valerio R


Please less math calculus in the quitzzes

創建者 yasemin c


Need to be more organized course items

創建者 REN F


Environment never get set up properly

創建者 Daniel J B O


Good refresh of Apache spark

創建者 LIN J


Video is too blur

創建者 Adrien P


très intéressant

創建者 SK H H


Can be better

創建者 Narendra b O



創建者 Julien P


Content was good even though very basic on statistics, certainly a good intro to Spark. However, final project/quiz was nearly insulting. Code was already written 100%, and most quiz questions were about copy/pasting literal output from pre-written code. Thought a mistake was made at first.

When students follow a course with a serious intent to learn, giving them a final quiz that barely tests their knowledge is a big downer, and makes students feel like they wasted their time learning all this stuff (even though they didn't). Students had proper access to all the code they needed to write 100% of the code themselves for the final quiz. Not sure why everything was done for them in the first place.

創建者 Anna A


If you have some experience with python or ML - it is an easy course to follow but seems not to be deep enough. If you are begginer in these field I do not reccomed the cource.

Not really systematic. The only thing it does: of you have and experience with python and ML it let you taske Spark. But all you skills seems to be not really used. Also the concepts of sparks seems to be hardly touched. I would call the course "Hello world"

if you are a begginner: you will not learn about ML or python. Some concepts are explained on simlpfied level that could lead to misleading.

Tests and actual topic seems to be unrelated

創建者 Vladimir G


Good day whoever reads this!

First of all I'd like to say thank you for the course. This topic is pretty interesting for me and I move through this course with interest. IF you would update videos according python 3.6++ as in notebooks it would be much easier to learn and get into things. Also final assignment seems a too easy.

Also quality of sound and videos varies from week to week, and sometimes even from lesson to lesson during one week.

Good day and best luck!