Meta Data Analysis with R
Meta Data Analysis with R is a practical, hands-on course delivered through live online classes, designed to help you analyze data systematically, extract insights, and build reproducible analyses using the R programming language.
This course goes beyond basic data handling and focuses on how R is used today in data analysis, research, and decision-making. Participants will work with real-world datasets and learn modern R workflows used by data analysts and researchers across industries.
📅 Class Schedule & Format
Start Date: February 12th 2026
Duration: 1 Session
Time: TBD
Mode: Live online classes
Platform: Google Meet
All sessions are interactive, featuring live coding demonstrations, guided practice, and opportunities to ask questions in real time.
What You Will Learn
- Understanding data and thinking like a data analyst
- Introduction to meta data and meta analysis concepts
- Setting up and working in R and RStudio
- Importing, cleaning, and structuring datasets in R
- Data transformation using modern R tools
- Exploratory Data Analysis (EDA)
- Data visualization using ggplot2
- Summarizing, analyzing, and interpreting datasets
- Writing clear, reproducible analysis workflows
Tools & Features Covered
- R and RStudio
- Tidyverse (dplyr, tidyr, readr, ggplot2)
- Data wrangling and transformation
- Exploratory Data Analysis (EDA)
- Data visualization best practices
- Summary statistics and analytical reporting
- Reproducible analysis principles
Who This Course Is For
- Senior secondary school students
- University and polytechnic students
- Working professionals
- Researchers and analysts
- Anyone interested in meta data analysis using R
No prior programming or data analysis experience is required.
What You’ll Be Able to Do After the Course
- Analyze and interpret structured datasets using R
- Work confidently with meta data and analytical summaries
- Clean and transform complex datasets
- Create insightful visualizations and reports
- Apply data-driven insights in research or business contexts
- Prepare for advanced analytics, research methods, or data science tools
Certificate
Participants who complete the course will receive a Certificate of Completion.