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Learning path checklist
Description - Data literacy learning path checklist
Followed by
Data literacy foundations
- What is Data? An Introduction to Data Terminology and Concepts
- Data quality in six dimensions
- Data Stewardship: An introduction to data standards and metadata
Supplementary videos on data literacy foundations
- FAIR data principles: What is FAIR?
- Data ethics: An introduction
- Data ethics part 2: Ethical reviews
- Step 1: Define - Find - Gather
- Gathering Data: Things to Consider Before Gathering Data
Followed by
Step 2: Explore - Clean - Describe
- Types of data: Understanding and exploring data
- Data accuracy and validation: Methods to ensure the quality of data
Supplementary videos on Step 2: Explore - Clean - Describe
- Statistics 101: Statistical bias
- Statistics 101: Proportions, rates and ratios
- Statistics 101: Exploring measures of central tendency
- Statistics 101: Exploring measures of dispersion
Followed by
Step 3: Analyze - Model
- Analysis 101, part 1: Making ananalytical plan
- Analysis 101, part 2: Implementing the analytical plan
- Analysis 101, part 3: Sharing your findings
- Analysis 101, part 4: Case study
Supplementary videos on Step 3: Analyze - Model
- Machine learning: An introduction
- Statistics 101: Correlation and causality
- Statistics 101: Confidence intervals
Followed by
Step 4: Tell the Story
- Data Visualization: An Introduction
- Telling the data story: How to create stories that matter