Modifying and Summarizing Data

Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level

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Overview/Description
This course covers data manipulation, including transforming XDF files, subsetting data, modifying variables, and converting data types. It also covers data summarization, including summary statistics and data exploration using Microsoft R.

Target Audience
All individuals who wish to understand key concepts in big data analysis and Microsoft R features including scientists, analysts, and statisticians

Prerequisites
None

Expected Duration (hours)
0.9

Lesson Objectives

Modifying and Summarizing Data

start the course

describe the process of data transformation in Microsoft R

identify important functions and arguments used to modify data in Microsoft R

identify how to subset and transform data in Microsoft R

identify how to create or modify variables in Microsoft R

identify functions to transform data

describe what predictive analytics is

identify use cases of machine learning

recognize main branches and use cases of predictive models

recognize what machine learning is and identify its use cases

describe supervised and unsupervised learning techniques

list important techniques in predictive analytics

list the main steps in building a predictive analytics solution

identify important machine learning techniques

Course Number:
df_abdr_a05_it_enus

Expertise Level
Expert