Hotline : 0811-9720-2000, CODEVA OFFERS OFFLINE AND ONLINE COURSES Office : 021 3002 0942 info@codeva.co.id
Select Page

Data Science with R: Data Analysis and Visualization

Fill Out The Form For FREE Classes And To View Codeva Program Packages

Beginner

Data Science with R: Data Analysis

and Visualization

This course is a 35-hour program designed to provide a comprehensive introduction to R. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which you will learn the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.

* Tuition paid for part-time courses can be applied to the Data Science Bootcamps if admitted within 9 months.

Course Overview

This course is a 35-hour program designed to provide a comprehensive introduction to R for Data Analysis and Visualization. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.

Prerequisites

  • Basic knowledge about computer components
  • Basic knowledge about programming

Certificate

Certificates are awarded at the end of the program at the satisfactory completion of the course. Students are evaluated on a pass/fail basis for their performance on the required homework and final project (where applicable). Students who complete 80% of the homework and attend a minimum of 85% of all classes are eligible for the certificate of completion.

Syllabus

Unit 1: Basic Programming with R

  • Introduction to R
    • What is R?
    • Why R?
    • How to learn R
    • RStudio, packages, and the workspace
  • Basic R language elements
    • Data object types
    • Local data import/export
    • Introducing functions and control statements
  • In-depth study of data objects
  • Functions
  • Functional Programming

Unit 2: Basic Data Elements

  • Data transformation
    • Reshape
    • Split
    • Combine
  • Character manipulation
  • String manipulation
  • Dates and timestamps
  • Web data capture
  • API data sources
  • Connecting to an external database

Unit 3: Manipulating Data with “dplyr”

  • Subset, transform, and reorder datasets
  • Join datasets
  • Groupwise operations on datasets

Unit 4: Data Graphics and Data Visualization

  • Core ideas of data graphics and data visualization
  • R graphics engines
    • Base
    • Grid
    • Lattice
    • ggplot2
  • Big data graphics with ggplot2

Unit 5: Advanced Visualization

  • Customized graphics with ggplot2
    • Titles
    • Coordinate systems
    • Scales
    • Themes
    • Axis labels
    • Legends
  • Other plotting cases
    • Violin Plots
    • Pie charts
    • Mosaic plots
    • Hierarchical tree diagrams
    • scatter plots with multidimensional data
    • Time-series visualizations
    • Maps
    • R and interactive visualizations
×