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Data Visualization and Transformation with R
This course is part of Data Science with R Specialization.
Course Cost
Free course
Beginner
Skill Level
11 Hours
Self-paced lessons
This course introduces data science and statistical thinking, focusing on data visualization and transformation for exploratory data analysis using R. Students will gain experience in exploring, visualizing, and analyzing data to understand natural phenomena, investigate patterns, and model outcomes. The course emphasizes reproducible and shareable data analysis techniques using RStudio, Quarto for reporting, and Git/GitHub for version control. Learners will work with packages from the Tidyverse, particularly ggplot2 for visualization and dplyr for data wrangling. Through lectures, live coding videos, and interactive exercises, students will tackle real-world inspired problems and datasets. The skills acquired prepare learners for various data-related careers, including data scientist, analyst, quantitative analyst, and statistician.
What you'll learn
Transform, visualize, summarize, and analyze data in R using Tidyverse packages
Create effective data visualizations using ggplot2 and the Grammar of Graphics
Perform data wrangling and transformation tasks with dplyr
Conduct exploratory data analysis on various types of data
Use RStudio for efficient R programming and data analysis
Create reproducible reports with Quarto
Apply version control to data science projects using Git and GitHub
Communicate data analysis results effectively through optional written projects
Skills you'll gain
This course includes:
3.9 Hours PreRecorded video
3 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 3 modules in this course
This course provides a comprehensive introduction to data visualization and transformation using R, with a focus on exploratory data analysis. The curriculum is divided into three modules: 1) Introduction to data science concepts and tools (R, RStudio, Quarto, GitHub), 2) Data visualization techniques using ggplot2, and 3) Data transformation and summarization using dplyr. Students will learn to create various types of plots, handle different data types, and explore relationships between variables. The course emphasizes reproducible research practices and introduces version control with Git and GitHub. Throughout the modules, learners will work with real-world datasets and problems, gaining practical experience in data analysis and visualization techniques.
Hello World
Module 1 · 3 Hours to complete
Data and Visualization
Module 2 · 2 Hours to complete
Visualizing, transforming, and summarizing types of data
Module 3 · 6 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Data Science with R Specialization
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Frequently asked Questions
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