- [Voiceover] When you're conducting a data science project,…there's an entire sequence of events that have to happen.…I refer to these as the data science pipeline.…Basically, there's four general categories of tasks.…In part one, you're doing planning.…In part two, you're doing data preparation.…In part three, you're doing modeling…or the statistical analysis of the data.…And in part four, you're doing follow up work.…We'll look at each of these very briefly.…First, part one, which is planning.…
There are four basic tasks involved here.…The first one is to simply define the goals,…what is it that you're trying to accomplish,…that way you can focus your efforts…and you know when you're done.…Second is organizing your resources.…So for instance, what data do you have available,…what machines do you have available.…More importantly, what people do you have available…and what time do they have available?…Third, once you've recruited a data science team,…you need to coordinate the efforts between those people.…
It's a social task but it's critical…
- 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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