- [Voiceover] When you're getting ready…to conduct a data science project,…one of the most important things…is to choose a metric or a measure of success.…That's because data science is goal-directed.…You need to know what your goal is…in order to tell when you've gotten there…or to know whether you have a viable answer.…Specifically, data science is action-oriented,…where the goal is to do something.…That's in contrast to, say, academic research,…which is knowledge-oriented, and the goal is understanding.…And I say this as a practitioner.…
Also, data science, the goals must be explicit…so they can guide your effort,…know what you're shooting for,…know if you're on your way to reaching it,…know if you need to make corrections.…And having a clear goal benefits the client.…It prevents frustration,…'cause they know what to expect from you.…And then, finally, it benefits the analyst, that's you,…because it gives you an efficient use of your time.…Now, the idea here is you want to be goal-directed,…but, at the same time, do be open to serendipity.…
- 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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