Prepare Data for Exploration Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This beginner-friendly course provides a comprehensive introduction to the foundational skills needed to prepare data for effective analysis. The course is structured into five core modules followed by a hands-on challenge, with each module requiring approximately 4 hours of engagement. Total time commitment is about 23 hours, allowing learners to progress at their own pace. Topics include data types, bias and ethics, databases, and data organization best practices. By the end, learners will apply their knowledge in a final project.
Module 1: Data Types and Structures
Estimated time: 4 hours
- Learn about structured data
- Explore unstructured data
- Understand different data types
- Identify common data formats
Module 2: Bias, Credibility, and Ethics
Estimated time: 4 hours
- Understand different types of bias in data
- Discuss the importance of credible data sources
- Explore data ethics principles
- Recognize privacy considerations in data collection
Module 3: Databases: Where Data Lives
Estimated time: 4 hours
- Explore how analysts use spreadsheets
- Understand the role of SQL in databases
- Examine datasets and their structures
- Describe functions and components of databases
Module 4: Organizing and Protecting Your Data
Estimated time: 4 hours
- Learn best practices for organizing data
- Apply principles for data consistency
- Understand methods for data security
Module 5: Course Challenge
Estimated time: 3 hours
- Apply skills in a hands-on project
- Prepare a dataset for exploration
- Demonstrate understanding of data preparation concepts
Module 6: Final Project
Estimated time: 3 hours
- Deliverable 1
- Deliverable 2
- Deliverable 3
Prerequisites
- No prior experience required
- Basic computer literacy
- Access to internet and Coursera platform
What You'll Be Able to Do After
- Understand key factors in data collection decisions
- Distinguish between biased and unbiased data
- Describe databases and their components
- Apply best practices for data organization
- Recognize ethical and privacy considerations in data handling