- [Voiceover] An important topic in data science,…in order to avoid getting yourself in trouble,…is big O and function performance.…This is important when times is of the essence.…The deal is this, functions that you can perform on…your data vary in speed.…The growth rate of a function, that is how much more time…it takes, is called it's order.…That's why it's called big O, O is for order.…Big O describes the growth rates and find out that…differences in growth rates can be dramatic and…sometimes counter-intuitive.…
So, for instance, some functions are very speedy.…You have what's called O(1), that's a constant…determinant for binary numbers, even or odd.…O(log(n)) that's a logarithmic function.…Or O(n) a linear function.…Again, those are all pretty quick.…Moderate includes O(n log(n)).…That's something that you would use for a fast four year…transform and actually is a very fast shortcut for…what it would be otherwise.…And then in terms of slow, and when I say slow,…I mean extraordinarily slow, there's O(n) to the square,…
- 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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