Courses
R Programming Course
This hands-on course teaches data visualization techniques using Python libraries for custom charts, Power BI for interactive dashboards, and Tableau for advanced storytelling with data. Students will learn to clean, analyze, and present insights from datasets, building skills for effective communication in business and analytics through practical projects and real-world applications.
About Course
Career Prospects
- R Programmer
- Data Analyst
- Data Scientist
- Statistician
- Machine Learning Engineer
- Quantitative Analyst
- Biostatistician
- Research Analyst
- Business Intelligence Analyst
- Financial Analyst
Course Curriculum
Module 1: Introduction to R
- Installation and Setup
- R Environment Basics
- Basic Syntax
- Data Types
- Variables and Operators
Module 2: Control Structures and Functions
- If-Else Statements
- Loops (For, While)
- Function Creation
- Arguments and Scoping
- Error Handling
Module 3: Data Structures in R
- Vectors and Lists
- Matrices and Arrays
- Data Frames
- Factors
- Strings Manipulation
Module 4: Data Import and Export
- Reading CSV Files
- Excel and JSON Handling
- Database Connections
- Writing Data Files
- Data Cleaning Basics
Module 5: Data Manipulation with dplyr
- Selecting and Filtering
- Mutating Columns
- Grouping and Summarizing
- Joining Datasets
- Piping Operations
Module 6: Statistical Analysis
- Descriptive Statistics
- Probability Distributions
- Hypothesis Testing
- Correlation and Regression
- ANOVA Basics
Module 7: Data Visualization with ggplot2
- Basic Plots
- Customizing Aesthetics
- Layering Geoms
- Themes and Scales
- Faceting and Coordination
Module 8: Advanced Topics
- Apply Family Functions
- Regular Expressions
- Date and Time Handling
- Parallel Computing
- Package Management
Module 9: R for Machine Learning
- Model Building Basics
- Classification Techniques
- Clustering Methods
- Model Evaluation
- Cross-Validation
Module 10: Projects and Applications
- Real-World Case Studies
- Shiny App Development
- Report Generation with RMarkdown
- Portfolio Building
- Deployment Strategies
Skills and Tools Covered
- R
- RStudio
- dplyr
- tidyr
- ggplot2
- shiny
- caret
- lubridate
- stringr
- data.table
- knitr
- RMarkdown
- readr
- DBI
Duration
1 Month
Cost
KES. 15,000