Week 3

Lecture 5: Sampling Case Studies and Complex Data Operations¶

• PDF Version | Google Slides Version

  • Learning Outcomes:

    • Identify sampling designs and bias in real research studies.

    • Apply advanced data manipulation techniques.

  • Activities:

    • Analyze case studies (Tuskegee Syphilis, Cambridge Analytica).

    • Perform complex data operations.

Lecture 6: Data Anonymization and Privacy Regulations¶

• PDF Version | Google Slides Version

  • Learning Outcomes:

    • Apply anonymization techniques in data.

    • Explain the role of privacy regulations in data ethics.

  • Activities:

    • Case study walkthroughs focused on ethical data handling.

Discussion 3: Ethical Considerations in Data Analysis¶

• PDF Version | Google Slides Version

  • Learning Outcomes:

    • Recognize data’s role in reinforcing power structures.

    • Understand the limitations and transparency issues in data-based decision-making.

  • Activities:

    • Engage in discussions on algorithmic bias and data ethics.

Lab 3: Advanced Data Manipulation and Privacy Techniques¶

• PDF Version | Google Slides Version

• Jupyter Notebook on Github

  • Learning Outcomes:

    • Apply data anonymization techniques.

    • Conduct complex data manipulations.

Project/Homework Part 3: Anonymization Techniques and Data Privacy¶

• Jupyter Notebook on Github

• Learning Outcomes:

  • Apply custom data anonymization techniques.

  • Process data with a focus on regulatory compliance.

• Activities:

  • Complete exercises related to data privacy and regulation.