Data analysis is crucial to accurately predict the performance of an application. This R Programming Fundamentals course begins by getting you started with R, including basic programming and data import, data visualization, pivoting, merging, aggregating, and joins.
Once you are comfortable with the basics, you will read ahead and learn all about data visualization and graphics. You will learn data management techniques such as pivots, aggregations, and dealing with missing values. With these various case studies and examples, this course gives you the knowledge to confidently start your career in the field of data science.
This is a hands-on guide that walks you through concepts with examples using built-in R data. Every topic is enriched with a supporting example that highlights the concept, followed by activities that will gradually build into a full data science project to showcase skills learned. You will perform an end-to-end analysis, starting a data science portfolio.
LESSON 1: INTRODUCTION TO R
- Using R, RStudio, and Installing Useful Packages
- Variable Types and Data Structures
- Basic Flow Control
- Data Import and Export
- Getting Help with R
LESSON 2: DATA VISUALIZATION AND GRAPHICS
- Creating Base Plots
- Interactive Plots
LESSON 3: DATA MANAGEMENT
- Factor Variables
- Summarizing data
- Splitting, Combining, Merging, and Joining Datasets
This course is for analysts who are looking to grow their data science skills beyond the tools they have used before, such as MS Excel and other statistical tools.
This course will require a computer system for the instructor and one for each student. The minimum hardware requirements are as follows:
- Processor: i3
- Memory: 2 GB RAM
- Hard disk: 10 GB
- Internet connection
- Operating system: Windows 8 64–bit
- R and RStudio
- Browsers (Google Chrome and Mozilla Firefox – latest versions)