- [Voiceover] When you're getting data…for your data science project,…you may have it in a spreadsheet,…you may have it in a relational database,…but it may also be on the web.…For that reason, you need to learn…a little bit about what I call web formats.…The idea here is that data science…thrives on the Internet…in terms of retrieving data…and in terms of sharing data.…There are a few things about this.…The first is HTML, or HyperText Markup Language.…The second is XML, or Extensible Markup Language.…
You need to be able to navigate HTML…
- 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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