R Programming for Data Analysis
Learning outcomes: Learn data cleaning, statistical analysis, and visualizations with R Books and materials: Included Estimated duration: 10 hours Pricing: USD 129.00
What You'll Learn
Module 1: Foundations of R Programming for Data Analysis
This module develops foundations and core concepts for R Programming for Data Analysis, with emphasis on Data Cleaning, Statistical Analysis, and Visualizations.
3 lessons
Lesson 1: Core Concepts: Foundations and Core Concepts
50mThis lesson focuses on foundations and core concepts within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Lesson 2: Practical Workflow: Foundations and Core Concepts
50mThis lesson focuses on foundations and core concepts within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Lesson 3: Guided Practice and Review: Foundations and Core Concepts
50mThis lesson focuses on foundations and core concepts within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Module 2: Tools, Systems, and Setup: Data Cleaning
This module develops tools, systems, and setup for R Programming for Data Analysis, with emphasis on Data Cleaning, Statistical Analysis, and Visualizations.
3 lessons
Lesson 1: Core Concepts: Tools, Systems, and Setup
50mThis lesson focuses on tools, systems, and setup within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Lesson 2: Practical Workflow: Tools, Systems, and Setup
50mThis lesson focuses on tools, systems, and setup within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Lesson 3: Guided Practice and Review: Tools, Systems, and Setup
50mThis lesson focuses on tools, systems, and setup within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Module 3: Workflow, Security, and Quality
This module develops workflow, security, and quality for R Programming for Data Analysis, with emphasis on Data Cleaning, Statistical Analysis, and Visualizations.
3 lessons
Lesson 1: Core Concepts: Workflow, Security, and Quality
50mThis lesson focuses on workflow, security, and quality within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Lesson 2: Practical Workflow: Workflow, Security, and Quality
50mThis lesson focuses on workflow, security, and quality within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Lesson 3: Guided Practice and Review: Workflow, Security, and Quality
50mThis lesson focuses on workflow, security, and quality within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Module 4: Practical Applications and Troubleshooting
This module develops practical applications and troubleshooting for R Programming for Data Analysis, with emphasis on Data Cleaning, Statistical Analysis, and Visualizations.
3 lessons
Lesson 1: Core Concepts: Practical Applications and Troubleshooting
50mThis lesson focuses on practical applications and troubleshooting within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Lesson 2: Practical Workflow: Practical Applications and Troubleshooting
50mThis lesson focuses on practical applications and troubleshooting within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Lesson 3: Guided Practice and Review: Practical Applications and Troubleshooting
50mThis lesson focuses on practical applications and troubleshooting within R Programming for Data Analysis. Learners connect core theory to practical expectations in Technology & IT, with emphasis on confident execution and measurable progress.
Enrollment
$129
Includes 12 lessons, learner enrollment, and access through the student account.