- [Voiceover] Calculus is in the foundation…of a huge number of things in data science.…Specifically, anytime you're dealing with rates of change…and you're dealing with optimization,…you need to be dealing with calculus.…There are three places in particular…that it comes in in data science.…Number one is it's part of the statistical foundations…of the practices, so for things like…least squares regression and probability distributions,…calculus is used to develop those.…Also, for change, measuring quantities…or rates that change over time…is inherently a problem for calculus.…
And then maxima and minima, any time you're trying…to maximize or minimize something,…you will generally be involving calculus.…Now there are two different kinds of calculus…that we generally need to be concerned with.…The first is differential calculus.…This is for rates of change at a specific time.…Sometimes people refer to it as the calculus of change.…There's also integral calculus, which is where…you determine a quantity of something at a specific time…
- 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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