Chevron Left
Volver a Fundamentals of Scalable Data Science

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

4.3
estrellas
1,942 calificaciones
•
431 reseña

Acerca del 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...

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.

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

Filtrar por:

151 - 175 de 433 revisiones para Fundamentals of Scalable Data Science

por Anton I N B

•
5 de mar. de 2020

I learned using Spark with RDDs on IBM Watson Studio 👍

por He Q

•
26 de ago. de 2019

easy and understandable, but the assignments lack depth

por Prashanth A

•
27 de jun. de 2020

Learned the data manipulation basics in data science

por Hemani B

•
12 de jun. de 2020

EXcellent to get in depth knowledge in data science

por Muntakimur R

•
15 de nov. de 2019

Very Informative course, thanks IBM for this course

por Ankur S

•
12 de nov. de 2019

One of the Best Courses available here on Coursera.

por Phasit C

•
2 de sep. de 2018

great introduction about Apache Spark and IBM Cloud

por Mukund S

•
4 de jun. de 2020

Really a good course for Data Science Programming.

por Philip L

•
28 de dic. de 2019

Love the content, simple and clear are the best.

por BENDIB H

•
23 de dic. de 2021

Very interesting course for the advanced skills

por Julien P

•
15 de sep. de 2019

Nice material! Especially the week on plotting.

por Tacio D

•
10 de jun. de 2019

Very good to follow. Instructor is very clear!

por Hrishikesh K

•
18 de ago. de 2021

One of the best basic course on data science

por Vivek K G

•
26 de jul. de 2020

Good Course Content and very well explained!

por Joshua A

•
28 de oct. de 2019

Gave excellent starting point for the course

por Jorge S A M B

•
13 de nov. de 2019

Conteúdo muito bom, atual e ótima didática!

por Ramil M

•
23 de ago. de 2018

Amazing course and especially instructor!!!

por Aishwarya A

•
19 de jul. de 2020

should help students in the specialization

por WALEED A

•
24 de ago. de 2020

It helps building skill. It is very good

por Alejandro P

•
22 de jul. de 2019

Thanks for the course, i learn so much.

por Himanshu Y

•
6 de jun. de 2020

I will not recommend it for beginners.

por Seif M M

•
5 de jul. de 2020

very good enhancement in data science

por Nabin R P

•
1 de feb. de 2020

well explained with relevant examples

por Joe-Kai T

•
18 de mar. de 2021

Very nice and well-organized course!

por GomathyShankar

•
30 de jun. de 2020

Excellent Instructions by Mr. Romeo.

Coursera Footer

Comienza o impulsa tu carrera profesional

Buscar temas populares

Cursos y artículos populares

Obtén un título de grado o un certificado en línea

Coursera

Comunidad

Más

Aprende en cualquier lado
Descargar en la App StoreConsíguelo en Google Play
Placeholder