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Comentários e feedback de alunos de Fundamentals of Scalable Data Science da instituição IBM

4.3
estrelas
1,837 classificações
399 avaliações

Sobre o curso

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...

Melhores avaliações

ZS
13 de Jan de 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.

AA
6 de Jan de 2020

A very nice introduction to Apache Spark and it's environment. As a bonus, it's also a very nice refresher to your basic statistics!!! Great course!

Filtrar por:

226 — 250 de 398 Avaliações para o Fundamentals of Scalable Data Science

por Jeff L J D

23 de Jan de 2021

THanks

por Dhaou B

1 de Jan de 2021

Thinks

por Venkadesh

27 de Nov de 2020

good

por Yash V

8 de Set de 2020

Good

por Sakshi U

24 de Jul de 2020

nice

por Rifat R

14 de Jul de 2020

Good

por Ankit M

1 de Dez de 2019

good

por Waleed M S A A A G

8 de Fev de 2019

ز

por Guido P

3 de Mai de 2020

The first course "Fundamentals of Scalable Data Science" on the specialization "Advanced Data Science with IBM" provides a good overview on theory, methods and tools you need for larg-scale data analysis. It requires basic to intermediate knowledge of Python and math. But it helps if you have experience beyond that to understand some ideas quicker and get the broader context.

Potential learners should know - as it is the normal thing with teaching/learning something - the teachers can't teach you something; you have to learn it. Means: spent some time beyond the time you need to consume the material from coursera. For example, I wrote five pages on the basics on statistics. It really helps! Again, the teachers organize a well well structured journey through the course material, but the just point to things that might be interesting.

On recommendation/request for improving quality of the provided videos: the are quite outdated. Date back to 2016/2017 and use Python 2 (which is not longer maintaned since 2020). Using the old python isn't too much of a problem, but it certainly does not help to learn effectively. The bigger problem is that the shown code is massively annotated with corrections and updates. These are all correct and helpful. But simply creating an updated video is way easier to consume. Just image a studend would submit his/her thesis as a draft plus a chain of 3 patches that have to applied on the thesis draft version. Not too handy, uhhm!?

por Alfredo P

6 de Mar de 2020

My 4-star review is based on the many errors the course has. The material s great and the instructor is very knowledgable and seems to be on top of the class, however, I did not get a single reply of the notes I posted in the forum.

Besides the structure, the class requires revision due to inconsistencies and errors. It is surprising that topics have not been updated after many comments in the discussion forum.

Overall for me, it was a great experience and great learning experience

por Scott B

2 de Mai de 2020

The content is great and applicable to industry. My only critique is that the coding assignments had been too simple. I would have preferred less hand-holding and more examples to work through to ensure the learner truly conceptualizes the process. With that said, it is easy enough for a learner to apply the process to other applications and understand how the pieces fit together for more real-world application.

por Moiz

28 de Dez de 2018

Overall i had a good experience with the course. The course touches a number of components of IBM Cloud platform, that includes IBM Watson Studio (online software development platform) and Node-RED (a flow based programming language for defining data flows). I am happy that this course gave me my first practical experience with Apache Spark. It took me around 10 days to complete this course.

por Pierre-Matthieu P

24 de Nov de 2019

I've gained plenty of interesting information and valuable hands-on experience. I had to work for it a little more than I should have, however. The lecturer has a strong accent, speaks very fast and the subtitles are mostly useless as they are wrong more often than not. If you take this course, be prepared to take plenty of notes and watch the videos several times.

por Nattapong T

19 de Jan de 2021

The course encompasses difficult and simple topics. For difficult ones, I have to follow "https://cognitiveclass.ai/learn/spark" as suggested by the instructor, and the course are really useful for understanding this course. Nevertheless, I found the programing exercise quite simple but good to recap what I have learned in the course. Thank you.

por Markochev S

27 de Mai de 2019

I would like to thank the authors of this course. It gives great introduction into Apache Spark and its applications in real problems. The only thing I would like to notice is that assignments could be a bit more complicated. Writing any code from scratch is much better for a future Data Scientist than just 'fill in' gaps in the existing code.

por Madison H

20 de Abr de 2020

the material in this course was interesting and I learned a lot in a short time. I now understand how to deal with big data using Spark which is exactly what I wanted. One thing I wish was different was the code in the submission notebooks. I wish the functions we wrote had parameters for example instead of basically just running a script.

por Ahmad R J

23 de Nov de 2019

I liked the course because it introduced me to new topics but it did not really go further as expected from an advanced specialization. Maybe when I finished other courses, I find out that it well prepared me for the rest. However, please provide more sample datasets, similar questions, and generally more practice.

por Jarryd

8 de Mar de 2020

A very slow beginning although that is to be expected so that the course can draw in people from a wide range of backgrounds. Still a little tedious for someone with a little more of a background. Very well organized and it seems like a great introduction to Spark / Pyspark for those just beginning with this tool.

por Shubham S

10 de Mar de 2019

The course is quite good. However, its not meant for absolute beginners. One needs to have a decent understanding of Python and SQL in order to follow the course and complete the programming assignments. However, the extra effort put towards learning how to program is well worth it

por am

14 de Abr de 2017

Nice Course. Going straight forward to the manipulations using spark, and giving a great overview on how to deal with IoT data in the Cloudant NOSQL platform. Would hope to see a new course where we can use MLLIB with massive IoT data to showcase the power of parallel programming!

por Sunil M

17 de Abr de 2017

I wish this was more extensive /detailed course and assignments little bit more complex. The moderator timely response was greatly lacking. If the course instructor is asking the students to try out RDD while the auto-grader depends on SQL, it should have been clarified.

por Hoàng M T

1 de Mai de 2020

Nice course. Inform the basic concepts of statistics.

Some of the code is not consistent (E.g. the week 4 assignment I have to remove the parameter of getListForHistogramAndBoxPlot() and getListsForRunChart() in submit cell in order to successfully submit).

por Igor O

1 de Set de 2020

It's a good course, good practices of IBM Watson Studio, Apache Spark and Python programming skills. Although would like to see more specific content about data science like methods and linear algebra libraries and techniques. But it was satisfatory, btw.

por Dushyant R T

15 de Jun de 2020

The course was designed some years ago and now it needs some update considering the technology has changed a bit. Even after all of that, the teachers are really good and they provide high-quality education. Really glad I could be part of this course.

por Victor W

31 de Out de 2020

Good course. However, there are a lot of silly mistakes in the videos, which is solved by "cloud text boxes". Does not look professional, rather re-record the videos. The videos are sometimes also pixelated. This could be improved significantly