A comprehensive educational curriculum designed to equip students with essential data literacy skills.
The Data Literacy Curriculum covers the full data lifecycle — from finding and understanding data, to extracting insights and communicating results effectively. Designed for undergraduate students and professionals entering data-driven fields.
| Module | Topics |
|---|---|
| Module 1 | What is data? Types and structures |
| Module 2 | Finding and accessing data sources |
| Module 3 | Data cleaning and preprocessing |
| Module 4 | Exploratory Data Analysis |
| Module 5 | Data visualization fundamentals |
| Module 6 | Statistical thinking and inference |
| Module 7 | AI and machine learning concepts |
| Module 8 | Ethical use of data |
By the end of this curriculum, students will be able to:
- Locate and evaluate data sources
- Clean and prepare datasets for analysis
- Create informative visualizations
- Draw evidence-based conclusions from data
- Apply ethical considerations in data work
- Undergraduate students (any discipline)
- Journalists and media professionals
- Business analysts and non-technical professionals
Author: Amr Eleraqi — Data Analyst | NLP Specialist | Machine Learning Expert | Educator
Affiliation: Toronto Metropolitan University, Ontario, Canada
