Chevron Left
Scalable Machine Learning on Big Data using Apache Spark(으)로 돌아가기

IBM의 Scalable Machine Learning on Big Data using Apache Spark 학습자 리뷰 및 피드백

3.8
별점
1,034개의 평가
270개의 리뷰

강좌 소개

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...

최상위 리뷰

AC
2020년 3월 25일

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
2019년 12월 11일

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.

필터링 기준:

Scalable Machine Learning on Big Data using Apache Spark의 269개 리뷰 중 151~175

교육 기관: Anna A

2020년 4월 17일

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

교육 기관: Vladimir G

2020년 1월 19일

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!

교육 기관: antonio g

2020년 5월 5일

In my opinion, the quality of the videos is not good, and while the teacher explains sharing his display, the display is fog and it is so difficult to see what is doing with the code.

In addition, some classes are recorded from a teacher´s car, I may understand that in some countries it could be usual, but in another one is a signal of non-professional behaviour.

교육 기관: Bea C

2020년 10월 27일

Decent overview of some of Apache Spark's features, but it seems the course team didn't really know what audience to aim for (some of the basic algorithms are reviewed but there's very little about SparkML Syntax, you're just supposed to figure it out). It would be nice to have a more hands-on approach (all the labs are just executing cells, no real exercises)

교육 기관: Julian S

2020년 5월 9일

Its only a part of a longer course. I would have prefered the longer version without getting the feeling of missing half of the story. The final Project did not feel like i did it my self. The answers of the last to questions in the correspondig test where strange (wrong?). Nevertheless I got the feeling that the full course would have been really nice ;)

교육 기관: Debayan P

2020년 6월 4일

The Course is complicated to understand for beginners. The introduction and many concepts could be more clarified at a slower pace. It would be better if the instructor could use a bit more time to teach the concepts and explain the concept of the Spark environment in general. Otherwise, the instructor has put a valiant effort.

교육 기관: Bo T

2020년 3월 29일

Some of the content could have been presented more clearly and recorded in the same manner consistently, few items seemed to repeat also while other are not covered well. The code walk thought should have been better explained and with less errors/clarifications which are later explained through video quiz or overlays.

교육 기관: Mitchell H

2020년 6월 8일

Good for learning the fundamentals of Spark, but unfortunately this course is becoming out of date. Many of the lectures need to be completely re-rerecorded to keep up with the evolution of spark. The quizzes are painfully easy and don't reinforce enough of the code. Needs more coding assignments. All in all, it's OK.

교육 기관: Aniket A

2020년 10월 20일

This is a quick, on-point introductory course for Apache Spark, not extensive, since not many industries are going for it, but the necessary concepts like Extract, Transform and Load also know as ETL is explained very well. The instructions are bit scarce, but the notebooks helps a lot. Overall, good!

교육 기관: Jesus M G G

2019년 12월 26일

-Some videos seem outdated, and one of them doesn't have all subtitles.

-The exercises sometimes uses some models or functions not covered in the videos

-I had some issues connecting to the Spark Kernel (it was working before and then stop working. It fixed it self after a few days)

교육 기관: Shivakumar K H

2020년 4월 22일

I felt that the course was filled with practicals which was explained very fast and without proper explaination. But the overall content was really good. It must have been more than 4 weeks and with proper explaination on coding part and including more related theories.

교육 기관: Mohammad S H

2020년 4월 6일

i like very much the Machine Learning, but the course was focusing to cover the whole functions,methods,logarithms...

but i was preferred to focus on few concepts and do more practicing on to understand more the course and to make it more beneficial in our job carrier.

교육 기관: Dylan W

2020년 5월 21일

I think this is a fine introduction to Apache Spark, but the notebooks don't really require much thought to complete. It'd be nice if they were a bit more instructive. And I'm not a big fan of lecture videos just showing the instructor type the code.

교육 기관: Scott P

2020년 2월 27일

The course material was clear but we are never really given any challenging practice exercises to do. The "project" at the end was litterely just running prewritten code - it would have been better if we got to write the code on our own.

교육 기관: José C

2020년 11월 17일

It seems that the course is not updated for some time.

What is described in the videos not always applies to the exercises.

Some mistakes are corrected with labels on the video.

In general the quality of the materials is not great.

교육 기관: Rashmin D

2020년 4월 22일

Its a good course but it duplicated content from the previous course in this specialized certification. Also speed for writing code is too fast in video. But some APIs and exercises are really good.

교육 기관: Mohamed A A

2020년 3월 24일

Overly, It is a well structured and oriented course, especially the practice part. However, the lectures could have been improved and made clearer. Thank you for all your efforts.

교육 기관: Andres I C R

2020년 11월 9일

The objectives on each class were not clearly defined, and the videos have a lot of errors that are partially corrected but will be good if the content of the course is reviewed.

교육 기관: Jesus C

2020년 7월 12일

The course teaches the very basics in a pretty simplistic manner. I think both videos and labs could be more descriptive and illustrative.

교육 기관: César A C

2020년 4월 26일

Very precise examples of parallel process to make predictions but may be not as demanding as other courses. The exercises where too easy.

교육 기관: Jasper v H

2020년 7월 24일

Good introduction to Spark, but very little playing around with ML.

Also, the UI for IBM Watson keeps changing and is really frustrating.

교육 기관: Diego D

2020년 7월 12일

This course is outdated, and there are a lot of errors in the presentation.

I think most of the videos in the course need to be updated.

교육 기관: Cristian M

2020년 11월 6일

Quite difficult to understand, since the videos have plenty of errors and the tutor goes really fast with no explanations some times.

교육 기관: Shivam S

2020년 11월 22일

Not enough coding opportunities provided. More Coding assignments and practice will be better and more content is very much needed.

교육 기관: Sanders L

2020년 11월 19일

Course needs some polishing. Video content seems to be outdated and not delivered in a format consistent with other IBM courses.