R Programming for Data Science Courseware (094025SE)
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.
Benefits
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.
Teaching This Course
The publisher has provided details here on how to teach this R Programming for Data Science course.
Outline
- Lesson 1: Setting Up R and Executing Simple Code
- Topic A: Set Up the R Development Environment
- Topic B: Write R Statements
- Lesson 2: Processing Atomic Data Types
- Topic A: Process Characters
- Topic B: Process Numbers
- Topic C: Process Logicals
- Lesson 3: Processing Data Structures
- Topic A: Process Vectors
- Topic B: Process Factors
- Topic C: Process Data Frames
- Topic D: Subset Data Structures
- Lesson 4: Writing Conditional Statements and Loops
- Topic A: Write Conditional Statements
- Topic B: Write Loops
- Lesson 5: Structuring Code for Reuse
- Topic A: Define and Call Functions
- Topic B: Apply Loop Functions
- Topic C: Manage R Packages
- Lesson 6: Managing Data in R
- 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
- Lesson 7: Analyzing Data in R
- Topic A: Examine Data
- Topic B: Explore the Underlying Distribution of Data
- Topic C: Identify Missing Values
- Lesson 8: Visualizing Data in R
- 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
- Lesson 9: Modeling Data in R
- Topic A: Create Statistical Models in R
- Topic B: Create Machine Learning Models in R
- Appendix A: Handling Issues in Code
- Appendix B: R Resources
Required Prerequisites
This course is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems.
A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language.
To ensure your success in this course, you should be comfortable with basic computer programming concepts, including but not limited to: syntax, data types, conditional statements, loops, and functions. You can obtain this level of skills and knowledge by taking the Logical Operations Introduction to Programming with Python® course.
You should also have at least a high-level understanding of fundamental data science concepts, including but not limited to: data engineering, data analysis, data storage, data visualization, and statistics. You can obtain this level of knowledge by taking the CertNexus DSBIZ™ (Exam DSZ-110): Data Science for Business Professionals course.
License
Length: 5 days | $271.67 per copy
What is Included?
- Student Manual
- Student Class Files
- Extra Trainer Files
- PowerPoint Presentation
