Course Description

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.

Data Science and Analytics with R

Student Name

Data Science and Analytics with R

Course Outline

Lesson 1: Setting Up R and Executing Simple Code
Lesson 2: Processing Atomic Data Types
Lesson 3: Processing Data Structures
Lesson 4: Writing Conditional Statements and Loops
Lesson 5: Structuring Code for Reuse
Lesson 6: Managing Data in R
Lesson 7: Analyzing Data in R
Lesson 8: Visualizing Data in R
Lesson 9: Modeling Data in R

Learners Outcome

Learner Outcomes
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

Night Sep 01, 2026

$1,97500

Course Code DAS300 Delivery   Date Sep 01 - Sep 17, 2026 Days of the Week Tue, Thu Time 5:30 PM - 8:30 PM (CST) Duration 6 Nights Hours/CEUs 18 hours / 1.8 CEUs

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