Data Analysis with R Programming Course Syllabus

Overview (80-120 words) describing structure and time commitment.

Module 1: Organize Data for More Effective Analysis

Estimated time: 5 hours

• Understand the importance of data organization in analysis
• Apply sorting techniques in spreadsheets
• Use filters to isolate relevant data subsets
• Implement sorting and filtering in SQL queries

Module 2: Format and Adjust Data

Estimated time: 4 hours

• Convert data types for consistency and usability
• Format data for clarity and analysis readiness
• Handle missing or inconsistent entries
• Combine data using basic SQL queries

Module 3: Aggregate Data for Analysis

Estimated time: 8 hours

• Apply functions to summarize data
• Use SQL syntax to aggregate from multiple tables
• Perform grouping and summarization operations
• Interpret aggregated results for decision-making

Module 4: Analyze Data to Answer Questions

Estimated time: 6 hours

• Identify key questions for data-driven insights
• Apply spreadsheet functions for calculations
• Construct SQL queries to extract meaningful patterns
• Validate findings through logical reasoning

Module 5: Final Project

Estimated time: 7 hours

• Import and clean a real-world dataset
• Organize and format data using spreadsheets and SQL
• Generate insights through aggregation and analysis

Prerequisites

• Basic computer literacy
• No prior experience with data analysis required
• Familiarity with navigating online platforms

What You'll Be Able to Do After

• Organize data effectively using sorting and filtering techniques
• Format and clean data for accurate analysis
• Write SQL queries to combine and aggregate data from multiple sources
• Apply functions in spreadsheets to perform calculations
• Answer business questions using structured data analysis methods