Process Data from Dirty to Clean Course Syllabus

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

Module 1: The Importance of Integrity

Estimated time: 3 hours

• Define data integrity and its significance in data analysis
• Identify common threats to data integrity
• Recognize issues related to insufficient data
• Avoid sampling bias in data collection and analysis

Module 2: Clean Data for More Accurate Insights

Estimated time: 5 hours

• Distinguish between clean and dirty data
• Identify common data quality issues
• Clean data using spreadsheets and basic tools
• Apply best practices for organizing and formatting data

Module 3: Data Cleaning with SQL

Estimated time: 4 hours

• Develop basic SQL queries for data retrieval
• Apply SQL functions to clean string variables
• Transform and standardize data using SQL
• Use SQL to handle missing or inconsistent data

Module 4: Verify and Report on Cleaning Results

Estimated time: 2 hours

• Describe methods to verify cleaned data
• Check consistency and accuracy after cleaning
• Document and report data cleaning processes

Module 5: Add Data to Your Resume

Estimated time: 3 hours

• Identify relevant data skills for resumes
• Showcase data cleaning experience professionally
• Build a resume section focused on data analytics

Module 6: Course Challenge

Estimated time: 3 hours

• Apply data cleaning techniques to a real-world dataset
• Use SQL and spreadsheet tools to clean and transform data
• Submit a cleaned dataset with a summary report

Prerequisites

• No prior experience required
• Basic computer literacy
• Familiarity with spreadsheets is helpful but not mandatory

What You'll Be Able to Do After

• Define different types of data integrity and identify risks
• Apply basic SQL functions to clean string variables
• Develop basic SQL queries for database use
• Describe the process of verifying data cleaning results
• Enhance your resume with data cleaning skills