Data science beyond data science

Objectives

• Understand how data science is applied in large-scale businesses like Amazon
• Explore the use of machine learning, prediction modeling, A/B testing, and market segmentation in such companies
• Discuss the ethical considerations around user data, including transparency and ownership
• Explore how data science is applied in other fields, such as healthcare, finance, and social sciences

Activity 11.1 Data science in the real world: Amazon case study [~40 min]

1. How might ML be used in this company?
2. Where do you think prediction models are used?
3. How might A/B testing be used?
4. What kind of data might be stored to improve prediction models?
5. Should the company be transparent about what data is collected and how it is used?
6. Who owns the data? Does the user have a say?
7. What are the ethical considerations around data collection and usage?

Activity 11.2: Data science in other sciences [30 min]

Consider the traditional hypothesis testing approach in science.

1. How has data science changed scientific practice?
2. How will the changes address the problems in science?
3. Are the results of data science better than traditional methods?