Chevron Left
Retour à Fundamentals of Scalable Data Science

Avis et commentaires pour d'étudiants pour Fundamentals of Scalable Data Science par Réseau de compétences IBM

4.3
étoiles
1,975 évaluations
442 avis

À propos du cours

Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU constraints are to most limiting factors when it comes to building advanced machine learning models. In this course we teach you the fundamentals of Apache Spark using python and pyspark. We'll introduce Apache Spark in the first two weeks and learn how to apply it to compute basic exploratory and data pre-processing tasks in the last two weeks. Through this exercise you'll also be introduced to the most fundamental statistical measures and data visualization technologies. This gives you enough knowledge to take over the role of a data engineer in any modern environment. But it gives you also the basis for advancing your career towards data science. Please have a look at the full specialization curriculum: https://www.coursera.org/specializations/advanced-data-science-ibm If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging. After completing this course, you will be able to: • Describe how basic statistical measures, are used to reveal patterns within the data • Recognize data characteristics, patterns, trends, deviations or inconsistencies, and potential outliers. • Identify useful techniques for working with big data such as dimension reduction and feature selection methods • Use advanced tools and charting libraries to: o improve efficiency of analysis of big-data with partitioning and parallel analysis o Visualize the data in an number of 2D and 3D formats (Box Plot, Run Chart, Scatter Plot, Pareto Chart, and Multidimensional Scaling) For successful completion of the course, the following prerequisites are recommended: • Basic programming skills in python • Basic math • Basic SQL (you can get it easily from https://www.coursera.org/learn/sql-data-science if needed) In order to complete this course, the following technologies will be used: (These technologies are introduced in the course as necessary so no previous knowledge is required.) • Jupyter notebooks (brought to you by IBM Watson Studio for free) • ApacheSpark (brought to you by IBM Watson Studio for free) • Python We've been reported that some of the material in this course is too advanced. So in case you feel the same, please have a look at the following materials first before starting this course, we've been reported that this really helps. Of course, you can give this course a try first and then in case you need, take the following courses / materials. It's free... https://cognitiveclass.ai/learn/spark https://dataplatform.cloud.ibm.com/analytics/notebooks/v2/f8982db1-5e55-46d6-a272-fd11b670be38/view?access_token=533a1925cd1c4c362aabe7b3336b3eae2a99e0dc923ec0775d891c31c5bbbc68 This course takes four weeks, 4-6h per week...

Meilleurs avis

EH

21 juil. 2021

Nice course. Learned the basics of a lot of different topics. Nice to do a large Data Science project in the last part. So you can apply all learned theory

MA

19 juin 2021

Great Course but this would have been even a better course if more concepts and details were covered in it. Anyways, still a great course for beginners

Filtrer par :

351 - 375 sur 444 Avis pour Fundamentals of Scalable Data Science

par Deleted A

11 févr. 2019

Can I get a badge?

par Bladimir P

24 sept. 2020

Great course!

par Ahmed T

10 mars 2019

Excellent :)

par Andrey O

10 août 2018

Good course!

par Marvin L

2 avr. 2020

it was good

par Fernando P

2 oct. 2020

Very good!

par Caroline L

27 avr. 2021

Too easy.

par Italo L

29 févr. 2020

Great

par Carlos F

29 avr. 2021

This was not especially well made. A number of the examples shown on videos don't necessarily work or are outdated with respect to the platform or the datasets you're working with. Perhaps, greater attention should be given towards guiding the student to the github repo were the notebooks are up to date and working properly. Otherwise a good course, definitely not introductory to cloud, if that's what you're looking for. There is some high level programming that I'm defnitely not prepared for but the notebooks are so complete that I did not have to apply myself so much. So on the one side I appreciate the ease of the notebooks but, on the other side, have some doubt as to the practical knowledge acquired. Hoping later courses in the specialization clear this out for me.

par Nikhil P P

8 févr. 2019

It was difficult to follow the IBM cloud setup since it was constantly changing, I couldn't understand the reason for using python2.7 since its only 10 months before it wont be supported by the community. Sometime instructors' pronunciations were not clear and and thus added extra confusion. However, instructor do actively participate in helping with discussions. Audio and video quality were also not very good. This course is a very basic introduction to IBM cloud and general stats. Prior knowledge of spark is useful. Overall the course is nice introduction to IBM cloud if one is interested.

par Jennifer K

11 mars 2021

This is a good introduction and overview to working with Spark. The assignments are very straightforward and I think that the biggest benefit is learning how to set up a work-station in IBM and working with your notebooks there. One thing that I think should be improved is the version of Python and Spark that is being demonstrated: the lectures should update to Python 3 and we also have Spark 3 by now; focus should be on data frames instead of RDD. Also, lots of links need to be updated because their references are deprecated and so no longer exist.

par Bayram

25 févr. 2020

This is a very basic course even if it's my first interaction with Apache Spark. For sure, it gives some information. But I found the timeframes stated too long. You feel like you'll get a lot of information. But a week of videos and readings and assignments can be done in 1.5-4 hours depending on your experience how much time you spend on assignments.

Also, there are many materials that are outdated. That should be fixed if this course carries the name of IBM.

par Rameez R

1 sept. 2020

The coding part is easy to comprehend but the course does not offer much opportunity to practice and learn the coding. The assignments are straight forward and doable. Sometimes it is hard to read the code in the videos even at 720p as it appears blurred. The subtitles cover some of the formulae shown at the bottom of the video and there are many mistakes in subtitles.

Overall, it is a good introductory course that gives you an idea of about Apache Spark.

par Joseph B J

27 avr. 2020

Good

The Course touches the important topics related to scalable data. The quizzes & assignments were challenging and the fun to solve.

Bad

Though the course touches the important topics, it does not go deep into it. Some of the codes provided in the video didn't work with the current version of python and spark. For example the code for finding the median. The Cognitive IOT app development method provided was broken and it wasn't the right way to do it.

par Eleni K

10 oct. 2019

I was really looking forward to this specialization but from the very first course I am really disappointed. The videos refer to various not updated information and then suddenly we are expected to do an assignment that was not at all explained in the course. I am not saying it is difficult, or not achievable but to be honest until now (week 2) it feels mostly like a waste of time.. Really sorry for this review.

par Moises D P A

2 juil. 2020

The course should be updated. It's hard work, but it's worthy. I'm sure students get confused a lot with the inconsistencies generated by the update of IBM Watson. So, there is some minus difference nowadays with what's being taught. Anyways, I think the content of the course is perfect to start. I learned satisfactory tools and ideas about how to handle big data.

par Jorge A V

17 janv. 2019

The idea and material behind the course is really interesting, albeit very basic. Some of the exercises and quizes, like the ones of interpreting plots are not very clear, since the plot quality is low. However, this is a very nice introduction to ML and IoT using Watson. Looking Forward for the next courses of the IBM Degree for advance data science

par Cedric K

29 août 2021

I​n my opinion, the slides for this course should include more graphics. Especially showing the relations between different tools and objects. As an example, the Video "Introduction to Cloudant" would profit a lot if some graphics showing the relations between it and Apache Spark would have been used instead of simply going over bullet points.

par Carolin W

6 mai 2022

- The provided Code and ressources are sometimes quite outdated. This lead's to Website Links, that are not up-to-date anymore, and errors within the programming environment when running the Code.

- The assignments are sometimes way to easy to solve, where a copy and paste of exercises is sufficient to successfully submit a "3 hour" Assignment

par Dmitry S

10 mars 2020

The course is called 'Fundamentals' and is indeed pretty basic. A good quick overview of the most basic concepts. Sometimes too basic to qualify for an Advanced course on Coursera. So, not really clear for which audience the course is.

Another fundamental course that does a better job is Spark Fundamentals from cognitiveclass.ai.

par Alex P

7 juil. 2020

Very very basic. Far away from advance. I did more than the whole course in just one lecture at my university (LSE). And that lecture at the university did not assume that we already got experience with Spark or python. I still give three stars because it is still quite ok, just far away from advanced.

par Sonja T

8 juil. 2021

Good material. Hard to understand the instructor's English. No professionally presented. Assignments are too easy, and we didn't get good, meaningful practice. Quizzes often address information that either the instructor failed to present well, if at all, or made mistakes on.

par Tony H

4 nov. 2019

I felt that, for a course labelled as 'Advanced', there were too many trivial questions in the quizzes and too much hand-holding in the programming assignments. That being said I did enjoy the course and learned quite a lot and look forward to the next one in the specialisation.

par Mohamed A T

29 janv. 2020

The course was great, the material and the assignments.

IBM Watson platform was easy to use.

But I can't see how this course is included in the "advanced" data science specialization.

Honestly I was expecting a more advanced course. But we'll see with the next ones.

par Csaba P O

9 sept. 2019

The content was OK, but I have expected more. Probably it was too basic for me. I would have been happy to see some more real life examples, like when to use the different statistics to solve real problems, not only the theoretical ones.