R Programming for Data Science (v1.0)
In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business.
Course Objectives
In this course, you will use R to perform common data science tasks.You will:
- Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data.
Agenda
- Topic A: Set Up the R Development Environment
- Topic B: Write R Statements
- Topic A: Process Characters
- Topic B: Process Numbers
- Topic C: Process Logicals
- Topic A: Process Vectors
- Topic B: Process Factors
- Topic C: Process Data Frames
- Topic D: Subset Data Structures
- Topic A: Write Conditional Statements
- Topic B: Write Loops
- Topic A: Define and Call Functions
- Topic B: Apply Loop Functions
- Topic C: Manage R Packages
- Topic A: Load Data
- Topic B: Save Data
- Topic C: Manipulate Data Frames Using Base R
- Topic D: Manipulate Data Frames Using dplyr
- Topic E: Handle Dates and Times
- Topic A: Examine Data
- Topic B: Explore the Underlying Distribution of Data
- Topic C: Identify Missing Values
- Topic A: Plot Data Using Base R Functions
- Topic B: Plot Data Using ggplot2
- Topic C: Format Plots in ggplot2
- Topic D: Create Combination Plots
- Topic A: Create Statistical Models in R
- Topic B: Create Machine Learning Models in R
FREE
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Course Type: Instructor Led