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

2,006 évaluations

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: 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 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 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... This course takes four weeks, 4-6h per week...

Meilleurs avis


13 janv. 2021

The contents of this course are really practical and to the point. The examples and notebooks are also up to date and are very useful. i really recommend this course if you want to start with Spark.


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

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51 - 75 sur 450 Avis pour Fundamentals of Scalable Data Science

par man c y

4 juil. 2019

Corrupted assignment, you will never pass assignment 2 as the assignment checker was corrupted. so disappointed. in fact nice lecture and tutor and videos.

par Prasad N

28 juin 2019

worse guidance and pathetic support - shame on COURSERA and instructors for this horrible situation. Have wasted enormous productive time on this

par Karthic N

3 janv. 2019

This is supposed to a course covering fundamentals , the course content lacks clarity and the instructors and mentors are not helpful either

par Maximilian F A

15 déc. 2021

Watson Studio was terrible and the general support was also terribe. Bit embarassig when youre trying to promote a tech platform!

par Sai S

23 mars 2019

very poor not even know the answers for the faculty

par Rohit B

3 juil. 2020

This course can be a bit tough at the start, especially if you (like me) are unfamiliar with big data, Hadoop and/or Spark. Fortunately, the instructor has given a lot of (optional) background material and introductory courses on CognitiveClass. I eventually took these free courses as it really helps strengthen your big data fundamentals, including RDD, HDFS and Spark.

Assignments are ok, definitely doable and easier than they could have been. Also, the instructor is using a really slick innovation of self-grading using a hash and a token generation rather than peer grading which can be heavily biased based on how they are graded.

Instructor is very knowledgeable and a very respected individual in the industry. I saw some students complaining about his accent. I personally found the English to be clear and grammatically accurate and never had issue in understanding. I live in Switzerland though and am used to the Schweitzerdeutsch accent.

All in all, an excellent course from a data science veteran in the industry!

par Rohan S

24 févr. 2019

This course takes you on a very structured path. It starts with the core concepts of spark and how is it important in the industry. The material along with the IBM cloud platform is a total bonus.

The assignments are challenging for a reason. They test your entire knowledge and makes sure that you pay careful attention to the material being delivered. In fact, while completing the assignments, you will find yourself looking through official library documentation for support; this is a good thing. Moreover, you also find yourself writing good quality code.

Romeo teaches the content in the simplest way possible. He explains the concepts with utmost care with adequate examples. The content on statistics is also very well laid out which helps you become a better decision maker.

Overall, the course was excellent and should suffice for anyone willing to learn spark and get familiarity with cloud technologies and Apache Spark.

par Oritseweyinmi H A

4 nov. 2019

Strong introduction into parallel computing and big data processing. Romeo's expertise on the subject matter, combined with his love for teaching was on show during this course. He did a great job explaining the theoretical aspects, and slowly but surely introducing us into the practical aspects as well, through the programming exercises. All in all, this has proved to be a high quality introduction into this space and I'm excited to take the next step, learn more and apply the fundamentals I have picked up here.

par Ted H

15 juil. 2019

A really good introduction to Apache Spark. The course has been changed around a lot to conform with the latest syntax and to make it easier to get to work with data. Many of the videos still refer to the old syntax but the examples have all been brought up to date. Students no longer need to generate their own data (with node-Red) but can immediately get to work on pre-generated data. All this change has made some parts of the course a little confusing, but a little perseverance will overcome these problems.

par Mayumu N N

25 avr. 2020

I have a master degree in Applied mathematics. I chose the specialization in Advanced Data Science. The course is really advanced and I like the way the teacher teaches and especially examines. This leads to reflection and absolute work. I am already going for the three remaining courses, and hope to obtain a professional certificate in Advanced Data Science. So far I enjoyed, so let see next1

par Daniel T

21 avr. 2019

Be careful when signing up for your IBM Cloud Instance and remember to shut it down when you're not using it. I ran out of free hours and unfortunately they're no longer free after the first 30 days which either makes it impossible or expensive to finish this course. Also, 30 days might mean an arbitrary 30 day billing cycle, perhaps starting on the 1st of the month.

par Humberto D

10 juin 2021

Very thorough explanations of code. Apache spark takes a little while to get used to, but the instructor does a good job motivating it and explaining all the python commands. The first course in this sequence does not cover any serious ML techniques. It's just an overview of some data analytics overhead needed for the remaining courses in this sequence.

par Alev K

26 sept. 2018

It was fun learning to me in Spark Python. Python is more attractive now, see it is not that complicated visualisation and calculation functions in it. I could manage SQL very well which helped me a lot. now i feel more confidant in Python.I use to like more R before now i see python advantages regarding R in terms of performance and cost effects.

par Saurabh M

24 juin 2020

Liked the quality and depth of the content. THe instructor is well-versed with the area and explanations are pretty clear, alongwith concrete use cases. The quizzes helped cement the finer theoretical points while the programming exercises helped me practice the concepts that were learnt!. Very good effort from the instructor. I learnt a lot

par Shakti s

28 déc. 2018

I would like to Recommend this course because this course Not only taught you the well developed Syllabus but also test your ability /skills to tackle problems in submitting Assignments and which i think is the exciting part and challenging.

that moment when your are dealing with the problem and finally solved that, that work really paid off.

par daniel b

17 déc. 2019

This class make me confident in using apache spark for data projects that I may need. I really enjoyed how simple and effective it was. Very practical, easy to follow, high level course. Can not wait until the next course. You should probably have some experience with data frames and lambda expressions before coming into this class.

par Eric C

16 avr. 2020

This course was fantastic. The videos and assignments were well thought out, logically organized, and revised when some details had changed since their creation. Details were accurate and deep enough to give context, without getting too technical. Moreover, the automated grading mechanism the instructor created is AWESOME.

par Shubham K

6 mai 2020

Very well organised material...Really liked the concept of dimension reduction and PCS.

Suggestion:- It is not for beginners so you may modify it as intermediate course.. Actually I find it advanced level course and I had gone through Spark Programming Fundamentals as you said.. And thus I was able to complete it...

par M B

23 juil. 2019

Extremely well done course!!!

I am not sure what the comments about bugs in the course are about; I did not experience any.

I've taken about a dozen or so courses on Coursera, and this was one of my favorites. Everything is well explained and well laid out.

I'm excited to take the remaining courses in the series :D

par Gusti R A

17 févr. 2019

This course is very recommended if you want to bring your Data Science skill to the next level. The instruction is very clear and easy to understand. The assignment is really challenging for me as the new comer in this Data Science world, but yeah, i finally can finished this course. You should take this course.

par jay g

12 août 2020

The course is a perfectly designed to get started with Apache Spark. You need to have good coding experience to do this course. The assignment style through Jupyter notebook is a very new and effective means of learning as you can practice the theory in real-time. Thank you for such a wounderful course.

par Angadvir S P

2 janv. 2021

The Assignments are a bit easy in terms of filling in the coding blanks. To increase the efficacy of the course and have an effective learning curve, it may help to write the entire code block for the students (with no or minimal hints). Resources (such as Python tutorial links) are helpful , however.

par Vikas J

28 juil. 2020

This course introduced me to working of Spark and different data science principles, it was a great discovery to find this course, I am hopeful after learning through the subsequent chapters of this course you will be fairly comfortable in writing big data pipelines and generate reports.

par Alok S

26 juil. 2020

This is an excellent course, I had no previous experience with Big Data or Hadoop but this course helped me learn lot's of new technologies and also it helped me learn about big data. Special thanks to the instructor @Romeo_Kienzler for this wonderful course.

par Alexander S

27 avr. 2020

I think it was pretty good. Despite some of the bad feedback in the forums (which I initially shared, since Romeo started out with a quite steep learning curve), ultimately I think this course conveys the basics of Spark and Data Science statistics well.