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

1,036 個評分
270 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.


101 - Scalable Machine Learning on Big Data using Apache Spark 的 125 個評論(共 269 個)

創建者 Lucas I S


Like the format of this course, which seems more laid back. Having said that, some of the assignments had some confusing portion, but need to acknowledge this is an intermediate course and not a beginner one. I also missed the part of the explanation that Apache Spark has its own tools vs. using Python's SciKit

創建者 이지양


Sources in the lectures were really great to understand what is Apache Spark and How to use it.

However, in some part of the lecture, I loss my way to understand what's going on here...

Anyway, at final course, I could review what I learned in this course and that will be a good guide to use Apache Spark.

創建者 Petros L


Very interesting course, learning about utilizing Apache Spark parallel processing and how to build ML models. Video quality was not satisfactory for viewing the described Python code and I had difficulties understanding the spoken language, fortunately the video's transcription helped.

創建者 Avashen P


Great course. There should probably be more coding tests where submissions get you a grade like some of the other Coursera coding courses.

Some of the coding in the lectures is a bit too quick, but that's probably just for because I have never used the Apache Spark syntax before.

創建者 Dhaivat H P


Very good teaching techniques, The professor explained everything well, The sound quality was dull on 2nd week's video and the accent was a bit tricky for me but the quizzes were good and if you code with him you'll be able to understand the concepts easily

創建者 Ali A


I like the course, but it fails to mention clearly how learning apache spark could help us. Also, it requires a certain amount of coding experience, I was able to finish it, but sometimes I had no idea what I was doing.

創建者 Rich P


It was surprisingly fast-paced. There were a few intuitive leaps, including a bad data reference on the final project, that were potential stumbling blocks, but I feel more confident having overcome them.

創建者 Sourab M


It is a good course for beginners in the domain of Apache Spark and Apache Spark ML. Programming assignments could have been better if they were applied to "Big Data" and not on toy datasets.

創建者 Miele W


Again a nice course that introduce you on Apache Spark Usage. Just a little suggestion, if you could insert a little tweak on how pass from spark to pandas and vice versa.

Enjoy :)

創建者 Dhivyarupini R


Teaching was clear and understandable. Only feedback would be I hope the lab work would be more hands on because I'm worried I don't pick up the concepts unless I type them out.

創建者 Robert v d V


Nice introduction to Big Data processing, No coding skill required. A little more focus on the theory would be nice as the Python coding exercises are a little redundant.

創建者 Giorgio G


Great tutorial overall.

Room for improvement: Fix the differences int the definition of kurtosis and skew between vide, test, examples (preferable the scipy definition).

創建者 Zaheer U R


It was a very interesting and skillful course. Thanks to IBM and Coursera for such a wonderful course. Special thanks to Mr. Romeo Kienzer for explaining it so well.

創建者 leonardo d


There are some issues with the normalization of the distribution moments. Everything else is good material to learn how to use apache-spark for the first time.

創建者 Julien P


Great notebooks. But the videos are getting old and are a bit obsolete compared to the contents in notebooks. I would have also appreciated more theory.

創建者 Chokdee S


Learning material is pretty good for getting started with Apache SparkML. Everyone who leaps into Scalable Machine Learning this is one of your choice

創建者 Brandon S C


I found this course incredibly beneficial. Moving forward, I would like to see a bit more explanation of concepts and few extra workable examples.

創建者 Stefan W


Course was nice and avoided peer-graded assignments (which I appreciate) but code was written in Python 2 which led to un-maintained code.

創建者 Shahtab A K


In some videos, it shows one thing in the video and then there is a prompt to follow another one. It gets a little bit confusing there.

創建者 Itamar A T


I found difficult to understand the concepts, for sure I must have to review the class.

Thanks for the dedication in helping us.


創建者 shashank s


for the last assignment we should have got the opportunity to code in the notebook instead of just running it and reporting results.

創建者 Sarath C G K


He has good knowledge. Though his language is ok , He covered very important topics in very short span of time with high quality

創建者 Lawrence K


Nice course with real details and opportunities to practice. We just need some more private study to cement skills learnt.

創建者 Shanmukha S S Y


I felt the week 3 and 4 were rushed a bit. But everything else was well done. It was like a well defined "pipeline" : )

創建者 Stephane A


Nice course. I really understand big data and how to manipulate data in data centers. I can use better Apache Spark.