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

3.8
1,130 個評分
295 條評論

課程概述

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...

熱門審閱

AC
2020年3月25日

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
2019年12月11日

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.

篩選依據:

226 - Scalable Machine Learning on Big Data using Apache Spark 的 250 個評論(共 295 個)

創建者 Cristina G

2020年4月14日

Unfortunately, there seems to be quite a few errors in the course. The only skills that you can actually take away is how to use Apache Spark. The machine learning and evaluation metrics explained in this course are riddled with errors. When writing to the teachers the only thing they say is they are checking on it and will get back to you and never do. I usually really like the IBM courses but this one was by far the worst MOOC I have taken so far.

創建者 Gaby B T

2020年4月6日

One of the worst courses I ever had.

1 - The whole thing seems rushed. A lot of mistakes!

2 - Confusing slides and exercises.

3 - Useless quizzes that provide no additional benefit to the learner.

4 - Uncompleted transcripts under the videos.

I do not recommend this course. Unfortunately, I have to complete it for a specialization, otherwise, I would have abandoned it.

創建者 andrew r

2020年11月22日

Out of date and confusing examples. Watson studio is hard to setup. Instructions were misleading. Incorrect information was taught. Accent sometimes hard to understand. Testing did not directly relate to course material and required external study. Tests within instructions videos did not pop up at natural intervals. Overall a disappointing experience.

創建者 Panagiotis P

2020年4月18日

The course is definitely one of the worst i had in coursera. Many issues with the sound (week 1) which in combination with the very hard accent of the tutor becomes unbearable for the first 2 weeks at least. The concepts are not explained enough. If you really want to learn choose something else.

創建者 Pietro D

2020年1月3日

The course is based on a previous version of IBM Watson platform that makes too many slides outdated. Too much time is dedicated to the definition and computation of basic statistical moments. The same information about Apache Spark is published on the project's website.

創建者 ANURAG G

2020年4月17日

The course has been forcefully put inside the IBM AI Engineering Professional Course, and does not fit in. The course instructor fails to explain the details in an effective way. Overall this course is not designed to be a part of this specific specialization.

創建者 Nils N

2020年3月24日

Maybe I do not have knowledge about Python, but a lot of things were not understandable for me. In addition, parts of the course are still shown in an older, out-of-fashion version of Watson. The shown code is not working in todays version

創建者 Nazmul H

2020年12月20日

This course and assessment method is not standard enough. It should have more practical exercises such as RDD programming, ML, SQL. Course project should have related to developing mini big data application with RDD to ML prediction.

創建者 Claudio C

2020年4月27日

The course should be reorganized. The video are taken from different courses and is not fluid follow it. There is very little in programming with functional programming. There are many concepts but not well explained. Not advided!

創建者 Juho H

2020年4月23日

The course teaches important concepts and skills on how to scale your machine learning algorithms - but it is in a desperate need of an overhaul to fix the numerous errors in the videos and workbooks.

創建者 Camilo F P

2020年9月9日

Did not like it that much, I´m not clear about spark and big data use cases for ML. The themes were variated and did not follow a line or path of learning.

創建者 Esteban H E

2020年1月28日

Not clear at all.

A lot of things are not explained, or explained in a confusing way. I learn more by researching what things meant than from lectures

創建者 Friscian V C

2020年7月7日

I dont like the instructor very much. I feel like his explanations are not the best and everything was just too fast.

創建者 vikram s

2020年7月3日

It's very difficult for a beginner (like me) to understand the whole science behind the concepts in Apache Spark

創建者 shiva k P

2021年1月11日

The content is quite old and full of mistakes. It would be great if the course material quality is improved.

創建者 Suman k s

2020年5月17日

Explanation not satisfactory and exercise also not so good.

too much issue in setup all these exercises.

創建者 Billy

2020年1月16日

focus too much on practical skills than the balance of concepts and implementations

confusing to follow

創建者 DK N

2021年1月20日

It was fine, but i couldnt understand clearly what the instructor want to explain.

創建者 tamador a

2020年6月3日

The course should give more in-depth assignments and also more explanation.

創建者 Harsh K

2020年4月12日

There is a lot of audio problem and content is also not updated.

創建者 Branly L

2020年2月14日

This course needs more spark towards the student.

Thanks.

創建者 Victor B

2020年3月22日

Videos are not informative.

創建者 kexin

2020年1月1日

A lot of errors in lecture.

創建者 Kirivitige A S F

2020年4月7日

So many errors in the codes. Especially the ones the instructor is showing us in lecture (his files run on python 2.7 and i'm running on python 3.6- has not updated some programs to run on python 3.6 with spark 2.3). He doesn't specify which file at the beginning of the video, nor does he have a link to the sample code he is showing us, nor does he specify which file to insert a spark session and to where can we find that specific file in GitHub. It's a huge confusion for a person who has zero programming knowledge and It took me a lot of time to fix the errors in the codes to get back on the lecture. I am utterly disappointed with this section. Didn't have any issue with the last session of this course. I wasted a lot of time. I'm utterly disappointed with this course.

However I must appreciate his lecturing is excellent. I was able to fully understand the theoretical part he explained. I did however fail to quickly understand the programming aspect due to multiple errors in the code.