Unit 1 — Introduction to Data Science and Its Applications
6 classes
1.1 Explore the Definition and Scope of Data Science
1.2 Identify Key Roles and Skills in Data Science
1.3 Examine Data Collection Methods and Sources
1.4 Analyze Data Processing Techniques and Tools
1.5 Investigate Real-World Applications of Data Science
1.6 Discuss Ethical Considerations in Data Science
Unit 2 — Understanding Data — Types, Sources and Formats
6 classes
2.1 Identify Different Types of Data
2.2 Explore Primary vs Secondary Data Sources
2.3 Distinguish Between Qualitative and Quantitative Data
2.4 Analyze Data Formats: Structured vs Unstructured
2.5 Assess Reliability of Data Sources
2.6 Apply Data Selection Techniques for Projects
Unit 3 — Data Collection, Cleaning and Organisation
6 classes
3.1 Identify Different Sources of Data for Collection
3.2 Explore Techniques for Effective Data Collection
3.3 Apply Data Cleaning Methods to Remove Inaccuracies
3.4 Standardise Data Formats for Consistency
3.5 Organise Data Using Appropriate Structures and Tools
3.6 Assess and Evaluate Organised Data for Analysis Readiness
Unit 4 — Data Visualisation Using Spreadsheets and Charts
6 classes
4.1 Understand Data Types for Effective Visualization
4.2 Create Simple Charts Using Spreadsheet Software
4.3 Enhance Charts with Titles, Labels, and Legends
4.4 Utilize Conditional Formatting for Data Insight
4.5 Explore Advanced Chart Types for Complex Data
4.6 Apply Data Visualization Skills through a Project
Unit 5 — Basic Statistics — Mean, Median, Mode and Interpretation
6 classes
5.1 Define and Explain the Concept of Mean
5.2 Calculate the Mean in Data Sets
5.3 Introduce and Differentiate Median from Mean
5.4 Calculate the Median in Various Data Sets
5.5 Understand Mode and Its Importance in Data Analysis
5.6 Apply Mean, Median, and Mode to Real-Life Scenarios