Algorithm
- set of rules to solve problems
- issues of data-driven policy-making: what is true for a group of people is not always true for individuals
Difference between data science and data analysis
- data science: focus on algorithms/methods development
- data analytics: application
Machine learning and AI
- Machine learning: classification&prediction learn from data
- AI: adjust and improve across iterations
Accidental data
- get data from open-source sources like social media platforms, instagram
Data analytics is subjective
- data cleaning
- data coding
- data collection
- interpret results
- what variables to put in the model