- [Voiceover] A critical topic within data science…are the ethical issues brought about…by the analysis of data in these formats.…Data science is a creative field…and often uses data in ways…that it wasn't really intended.…So, you get a few issues that are big.…The first of these is privacy.…Confidentiality is a major issue.…And that's information that shouldn't be shared…even if it's not anonymous.…And the reason this is important is because…data science often relies on data sources…that weren't designed for sharing.…
The second thing is anonymity.…The HIPPA regulations have been revised…to make it much harder to identify…unique individuals within data.…Now, that means if you're using…publicly-available data,…it may be much closer to anonymous.…On the other hand, proprietary data,…where you're working for a client…and they're giving you their own data,…that may still have identifiers,…and in that case, the data is no longer anonymous.…Anonymity is a major, central element…of research ethics, and is something…that needs to be considered carefully.…
- Assess the skills required for a career in data science.
- Evaluate different sources of data, including metrics and APIs.
- Explore data through graphs and statistics.
- Discover how data scientists use programming languages such as R, Python, and SQL.
- Assess the role of mathematics, such as algebra, in data science.
- Assess the role of applied statistics, such as confidence intervals, in data science.
- Assess the role of machine learning, such as artificial neural networks, in data science.
- Define the components of effective data visualization.
Skill Level Beginner
1. What Is Data Science?
2. Fields of Study
Ethical issues2m 39s
4. Data Sources
5. Data Exploration
8. Applied Statistics
9. Machine Learning
Next steps2m 17s
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