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学生对 IBM 提供的 Fundamentals of Scalable Data Science 的评价和反馈

4.3
1,827 个评分
397 条评论

课程概述

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...

热门审阅

ZS
Jan 13, 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
Jan 6, 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!

筛选依据:

76 - Fundamentals of Scalable Data Science 的 100 个评论(共 397 个)

创建者 Savan R

May 23, 2019

Covers exactly what is required for data science using spark in case IoT data applications and the fundamentals required for the advanced data science topics . I am happy with the course and the topics that I have learned so far!

创建者 Norman W

Feb 8, 2021

Challenging, with a strong introduction to Data Science concepts an practical application. Valuable insights for how to get meaning from data. Enthusiastic instructor who clearly enjoys teaching and sharing about this subject.

创建者 Mark M

Apr 20, 2020

I learned a good amount about Apache Spark, IBM Watson, and integrating both with Python.

I liked the shorter videos with multiple checkpoints throughout and found the assignments and tutorials to be sufficiently challenging.

创建者 Yair G

Nov 1, 2020

As someone who has taken dozens of online courses across many platforms, I very much enjoyed this course and I am looking forward to continuing the specialization! Well structured and assignments that actually made sense.

创建者 Mirza A A B

Jun 22, 2020

pretty good course for a beginner new to big data analysis. I am glad that I got to know about the apache spark and learn it as a part of this course on the IBM Watson platform. will look forward to further modules.

创建者 Joshua L

Jun 22, 2020

Great course that covers some of the fundamentals of advanced data analytics. I use some of these techniques (like PCA) in my career for discovering defects in devices. This is a great starting course.

创建者 Youdinghuan C

Jun 12, 2020

Concise course. Has its challenging aspects, but overall was clear. The best part is the programming assignment and tutorials: great hands-on introduction to IBM Watson Studio with manageable examples.

创建者 Edi W

Feb 17, 2020

Nicely arranged course. However, both assignment on week 4 should be rechecked to make sure that it could run as exercise to student. Also, please make sure that the video is up to date and less error.

创建者 Zeeshan S

Jan 14, 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.

创建者 Xilong W

Apr 11, 2017

Very useful courses to take if you are beginner of data science. The course was not detailed enough sometime. But you will surely get a global view of IOT data analysis after this courses.

创建者 ABIR E

Mar 26, 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

创建者 Adamya

Jan 7, 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!

创建者 G' K

May 6, 2020

Its a great experience especially with this course. I appreciate Romeo the way he designed the assignments. It brings out the clear understanding.

创建者 Humberto T

Dec 7, 2020

A nice introduction to ApacheSpark on Python while learning about the fundamentals of Statistics and Dimensionality of data for Machine Learning

创建者 HONEY T

Sep 12, 2020

It feels really good when you get to learn something new and Coursera helped me to achieve something and learn something new and good.

创建者 Vaibhav S

Aug 24, 2020

great learning and thank you so much for great content for such topics. i loved this course and enjoyed a lot during learning.

创建者 Tee H L

Dec 16, 2019

I really like this learning method from IBM especially the instant quiz just to make sure I understand the important points.

创建者 Preyash G

Apr 20, 2020

This is one of the best course I came across so far, please keep on updating and adding such courses, Thank You

创建者 adele c

Apr 9, 2021

Easy to follow, excellent explanations, IBM Watson notebooks super easy to run and follow (maybe too easy)

创建者 Sabestin N

Jul 14, 2020

Thank you so much for giving good exposure. for a basic starting machine learning career for student.

创建者 SHAHAPURKAR S M

Apr 29, 2020

Excellent teaching by the instructor and user friendly well designed assignment platforms and quizzes

创建者 Nawas N

Jun 19, 2020

The course was well crafted enabling one to apply knowledge acquired in easy way in the assessments.

创建者 Edoardo B

Jun 29, 2018

A wonderful course enjoyable and useful for my professional objective. Very thanks to the teacher

创建者 Elena F

Apr 28, 2020

Nice and well-structured introduction to Spark; clear, accessible and useful quizzes / exercices

创建者 Dhinson G D

Oct 1, 2019

I love the course content. Simple but very informative and provides good practical exercises.