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Opiniones y comentarios de aprendices correspondientes a Fundamentals of Scalable Data Science por parte de IBM

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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...

Principales reseñas

MA
19 de jun. de 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

AA
6 de ene. 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!

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376 - 400 de 414 revisiones para Fundamentals of Scalable Data Science

por Mohammed E

23 de feb. de 2021

The Course is quite basic, however it's useful in building up my knowledge

por Saif U

23 de jun. de 2020

The structure and material quality needs complete revision and improvement

por Xuan H N

2 de ene. de 2020

More coding please. One doent learn much just by filling out couple words

por Israel F

14 de dic. de 2020

Too many theory for such little practice. But not bad as an intro.

por Gianluca G

1 de jun. de 2020

A little more deep tutorials on spark language would be useful

por Francesco d C

4 de dic. de 2019

the assignments could have left more freedom to the student.

por shubo w

5 de sep. de 2020

Feel like the lecture and assignment are a bit irrelevant

por Robert H

26 de mar. de 2020

Nice subjects notebooks could be more in-dept

por IVAN I

16 de abr. de 2021

too easy, programming part too stupid

por 吴芃

14 de mar. de 2020

seems it is not well prepared

por Feng L

26 de dic. de 2019

too simple

not advanced

por Anderson E A G

25 de dic. de 2020

it's not enough clear

por Leyre

7 de dic. de 2019

Low level

por Lei Z

15 de jun. de 2021

N​ot very good. There is no logic in the lectures and the exercises. I have been a reputable pure mathematician for many years. Taught several linear algebra courses. But when I hear the "linear algebra" taught by Romeo Kienzler I am deeply confused, completely don't know what he wanted to say. The exercises on "linear algebra" are equally bad, confusing, with no logic.

por Ian H

10 de jul. de 2020

A disappointing amount of the material presented is out of date (e.g. what environments to use, Watson vs 'Data science experience' )--while fine for some cases, it too frequently borders on intrusive at best to desperately opaque at worst. Clarity of presentations could also be greatly helped. Perhaps focusing more on the why? and so what? aspects would be helpful

por Aner W

11 de feb. de 2021

The explanations are not clear enough- the rational for using spark is not clear enough (missing context explanation, etc)

missing written lecture notes (in bullets- summariezed)

It would be helpful if the lecture text would be integrated in the video itself and not below the video presentation- harder to follow

por Erik A

31 de ago. de 2020

The videos are fuzzy, extremely outdated, and don't match up with the actual projects. I couldn't pay much attention to them. Projects were good though.

por Markus W

22 de sep. de 2019

Romeo does a very good job of explaining things!

However, the programming assignments are too easy to learn anything from.

por Zhao Q D

9 de mar. de 2020

Both exercises and programming tests are too easy. It should be real programming instead of filling in the blanks.

por Jason M

14 de may. de 2020

very simple. homework not challenging enough - just repeating the demos almost exactly.

por Brian A P

1 de may. de 2020

The course content is not well structured and at times very confusing.

por Paulo R C D S

4 de may. de 2020

Very basic and Spark exercises are too easy to learn useful skills

por Yew C L

15 de oct. de 2020

Not really fundamental. Beginner will have difficulty to learn.

por Nima

4 de jun. de 2020

Big data materials are less discussed specially coding sections

por RAHUL C

21 de ago. de 2020

The course feels old now. Not much interactive.