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学生对 IBM 提供的 Scalable Machine Learning on Big Data using Apache Spark 的评价和反馈

1,223 个评分
310 条评论


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...


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.

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.


301 - Scalable Machine Learning on Big Data using Apache Spark 的 312 个评论(共 312 个)

创建者 wasim m

May 22, 2020

the worst course by ibm

my confidence level goes down after taking this course

创建者 Yutaka R

May 25, 2020

If the video without subtitle, I swear I can't understanding the lecture....

创建者 lorenzo a

Apr 3, 2020

It really feels like the course was prepared in a bit of a rushed fashion.

创建者 Mariam A

Mar 2, 2020

Useless course, waste of time, but i had to take it for the certificate.

创建者 Fernando G

Dec 13, 2021

Very low quality course, not recommended. I expected better from IBM

创建者 Nazim U S

Jun 27, 2021

One of the worst course ! Struggling to understand Romeo's accent.

创建者 gurdeep s

May 25, 2020

Not much explanation regarding concepts. Disappointed.

创建者 Arjan P B

May 3, 2020

What a mess, please remove this course right away.

创建者 Annejet t K

Jun 17, 2020

Old course not compatible with python 3.7

创建者 harshad j

Sep 2, 2020

WAS not upto that

创建者 Giuseppe C

Mar 28, 2020

very bad teacher

创建者 Abish P

Aug 14, 2020

Not that good