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Using Data to Find Data: Correction & Categorization

Using Data to Find Data: Correction & Categorization


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Data professionals working with various data management systems must be able to implement data correction by using R and have a good understanding of data and data management systems. In this 12-video course, learners explore how to apply and implement various essential data correction techniques; to follow transformation rules; and to use deductive correction techniques and predictive modeling by using critical data and analytical approaches. Learn more about data wrangling, essentially the process of transforming and mapping data into another format to ensure that data are appropriate for analytical requirements. Along the way, you will learn key terms and concepts, including how to design data dimension; dimensional data design; cleansing data, and cleansing data with Python; data operations for fact finding; and common data operations for fact-finding. Next, learn about data categorization with Python; data visualization in general; and data visualization with Python. In a concluding exercise, you create a series data set by using Python; create a data frame using the series data; and, finally, calculate the standard deviation of the data frame.



Expected Duration (hours)
0.9

Lesson Objectives

Using Data to Find Data: Correction & Categorization

  • Course Overview
  • describe approaches for facilitating data management with emphasis on data layout
  • recognize the benefits of dimensional data design
  • demonstrate the methods of cleansing data using Python libraries
  • describe how to facilitate common operations of finding data facts using Python
  • demonstrate data wrangling approaches using Python
  • recognize how to facilitate variance measurement using Python
  • specify the importance of data categorization and describe data categorization types
  • work with classification to facilitate data categorization using Python
  • implement data categorization using the clustering
  • use Python to facilitate data visualization and depict data graphs
  • wrangle and categorize data using Python and clustering
  • Course Number:
    it_dsudfddj_02_enus

    Expertise Level
    Intermediate