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R Programming for Data Science and Analytics
R is a functional programming environment for business analysts and data scientists. It's a language that many non-programmers can easily work with, naturally extending a skill set that is common to high-end Excel users. It's the perfect tool for when the analyst has a statistical, numerical, or probabilities-based problem based on real data, and they've pushed Excel past its limits. In this course, you will work in a hands-on environment, learning R and its ecosystem, and where it’s a better a tool than Excel.
Course Overview
- Intermediate-level experience in a data analyst or data scientist field.
- Prior experience working with programming languages.
8890 McGaw Road
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Chicago, IL 60661
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Plano, TX 75024
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Tempe, AZ 85281
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Learning Objectives
- Define basic data science processes
- Identify and define R programming variables, types, loops, scalars, vectors, and matrices
- Perform string and text manipulation in R
- Identify and employ R lists & functions
- Use R DataFrames and file I/O
- Read data from files and perform data preparation
- Perform data visualization using a range of plotting functions
- Use Dplyr for data exploration
- Create statistical models with R
- Use linear and logistic regressions
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.