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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

ZS
13 de ene. 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.

AE
25 de mar. de 2021

It's good but it really requires someone who knows and even master Spark Apache(+SQL fundamentals) so that you can follow and understand and take advantage of the course

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276 - 300 de 424 revisiones para Fundamentals of Scalable Data Science

por Bruno N

3 de sep. de 2018

Very good course for a hands on overview introduction to the topic, and the associated tools (particularly Apache PiSpark).

Some issues with the auto grader encountered sometimes.

por Luca P

13 de sep. de 2021

Very clear explanations. Tests not too difficult. Sometime too easy for an "advance" course. I liked it and I am looking forward to learn in the next sections of the program.

por QUAZI M T M

5 de jul. de 2020

There should be some links that are helpful towards this course, as it is an intermediate course, what courses are available in Coursera prior to this as a beginner lesson.

por Nora I

19 de nov. de 2020

The difference between rdd, dataframe and sql.spark could be more clear in the practical sense. But all in all excellent course. A boost in my Data Scientist profile!

por Gouri K

12 de nov. de 2019

Good overall,instructor was very good,but I feel more examples could be used especially when explaining multidimensional vector space and such basics of graphs

por Ivan J M

2 de nov. de 2019

There are a lot of not updated sections, sometimes it confuses me because in some videos he talks about how we will use Node RED but then we don't use it.

por Gerardo E G G

26 de jun. de 2020

Great Course!

I would like to suggest to update the videos in order to reflect the operations in Python 3.x rather than 2.x but everything else was great!

por Muzamal A

10 de may. de 2020

Romeo is a great instructor and I love his lectures, however some of the quiz questions are very trivial and aren't explained on his video tutorials...

por Lucas M B

2 de dic. de 2019

Seria ótimo se atualizassem o conteúdo do vídeo para reproduzir a versão atual do sistema e do Python, porém em teoria o conteúdo não deixou a desejar.

por Parth G

4 de oct. de 2020

A bit on the easy side especially if you are proficient with SQL. But otherwise a decent into to spark and nice flavour of data analysis with python.

por Eric J

9 de feb. de 2017

Really good course to provide an overview of working within IBM's cloud platform offerings. This course provides the basics of ApacheSpark as well.

por Thomas M

12 de sep. de 2020

Pretty fun introduction, assignments were moslty copy-paste from instruction videos, so you don't get to 'learn' the right way in my opinion

por Kevin A H L

30 de jul. de 2020

I taught the course would be more advanced. Terminology is confusing at first, but besides that, the assignments aren't so challenging.

por Umer A B

18 de mar. de 2017

The Grader template in the beginning is very confusing when doing first assignment. The response from Instructor should be quick.

por Mortaja A

4 de ene. de 2019

structure and instruction to setup of ibm clound and ibm watson needs improvement. overall good instructions and flow.

por Tamer M

24 de sep. de 2019

Most of the video's subtitles need to be synced, it was hard to fully understand the Indian accent without subtitles.

por Jaydeep K R

23 de jun. de 2020

It was a good overview of the large scale data but I would be more interesting if they had provided more Practice.

por Norman F

13 de ene. de 2019

Some errors like lambdas are not working anymore with Python, some typos like in Assignment 4.1 and missing steps.

por matthew w

15 de mar. de 2021

Content (videos and quizzes were great). I would have preferred the coding assignments to be more challenging.

por Jithil S

5 de jul. de 2020

A pretty good starter course for apache spark although the software version used in this course is outdated .

por Nicolas G J

8 de abr. de 2021

The explanations sometimes are not clear, but with some readings and searching the projects can be resolved.

por Ricardo L

5 de jun. de 2020

The content is good, very easy to pass. But too basic. You almost no learn anything about spark dataframes.

por Vinayaka S

21 de ene. de 2021

Assignments need proper instructions. Also audio quality of lesson is not proper. Everything else is nice.

por Rodrigo V G

23 de ago. de 2020

A very general review of Spark, Statistics and Data Visualization. Some great insights were given, tough

por ANAND G 1

14 de jun. de 2020

A good introduction to the steps to be taken to handle huge data sets. Surely would recommend to others.