Process Data from Dirty to Clean

Process Data from Dirty to Clean

课程
en
英语
22 时
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来源
  • 来自www.coursera.org
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  • 6 序列
  • 等级 介绍

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课程详情

教学大纲

WEEK 1: The importance of integrity
As you start thinking about how to prepare your data for exploration, this part of the course will highlight why data integrity is so essential to successful decision-making. You’ll learn about how data is generated and the techniques analysts use to decide what data to collect for analysis. And you'll discover structured and unstructured data, data types, and data formats.

WEEK 2: Sparkling-clean data
Every data analyst wants clean data to work with when performing an analysis. In this part of the course, you’ll learn the difference between clean and dirty data. You’ll also explore data cleaning techniques using spreadsheets and other tools.

WEEK 3: Cleaning data with SQL
Knowing a variety of ways to clean data can make an analyst’s job much easier. In this part of the course, you’ll check out how to clean your data using SQL. You’ll explore queries and functions that you can use in SQL to clean and transform your data to get it ready for analysis.

WEEK 4: Verify and report on your cleaning results
Cleaning your data is an essential step in the data analysis process. Verifying and reporting your cleaning is a way to show that your data is ready for the next step. In this part of the course, you'll find out the processes involved with verifying and reporting data cleaning as well as their benefits.

WEEK 5: Optional: Adding data to your resume
Creating an effective resume will help you on your data analytics career path. In this part of the course, you’ll learn all about the job application process with a focus on crafting a resume that highlights your strengths and applicable experience. Even if you aren't applying to jobs yet, it's still a good time to improve your resume. It's like spring training for the first season in a major league–you don't want to miss it!

WEEK 6: Course challenge
Prepare for the course challenge by reviewing terms and definitions in the glossary. Then, demonstrate your knowledge of the importance of sample size, data integrity, and the connection of data to business objectives during the quiz. You will also have an opportunity to apply your skill with data cleaning techniques in both spreadsheets and SQL. Finally, document, report on, and verify your data-cleaning process and results.

先决条件

No prior experience with spreadsheets or data analytics is required. All you need is high-school level math and a curiosity about how things work.     

讲师

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编辑

谷歌是一家公司,由谷歌搜索引擎的创始人拉里-佩奇(Larry Page)和塞尔吉-布林(Sergueï Brin)于 1998 年 9 月 4 日在加利福尼亚州硅谷的谷歌车库创立。

该公司主要通过其搜索引擎的垄断地位而声名鹊起,先是面临 AltaVista 的竞争,然后是雅虎和必应的竞争。此后,该公司进行了一系列收购和开发,如今拥有许多著名的软件产品和网站,包括 YouTube、Android 手机操作系统以及 Google Earth、Google Maps 和 Google Play 等其他服务。

平台

Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。

Coursera与顶尖大学和组织合作,在线提供一些课程,并提供许多科目的课程,包括:物理,工程,人文,医学,生物学,社会科学,数学,商业,计算机科学,数字营销,数据科学 和其他科目。

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