Teaching you the probability theory necessary to think like a data scientist. You will learn about expected values, combinatorics, Bayesian notation, and probability distributions.
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Data science is based on statistics and statistics steps on the foundations laid by probability. This course will help you master the probability theory necessary to think like a data scientist. You will learn about expected values, combinatorics, Bayesian notation, and probability distributions.
Skills you will gain
What You'll Learn
Probability and statistics are essential when working with predictions. With this course, you will master probability theory and learn how to apply it as a data scientist.
- The Basics of Probability Free5 Lesson 25 Min
- Combinatorics Free12 Lesson 43 MinFundamentals of Combinatorics Free Computing Permutations Free Solving Factorials Free Variations with Repetition Free Variations without Repetition Free Combinations without Repetition Free Combinations with Repetition Free Symmetry of Combinations Free Combinations with Separate Sample Spaces Free Winning The Lottery Free Summary of Combinatorics Free Practical Example - Combinatrics Free
- Bayesian Inference Free12 Lesson 54 MinSets and Events Free The Different Ways Events Can Interact Free The Intersection of Two Sets Free The Union of Two Sets Free Mutually Exclusive Sets Free Dependent and Independent Events Free Conditional Probability Free Law of Total Probability Free Additive Law Free Multiplication Rule Free Bayes Rule Free Practical Example - Bayesian Inference Free
- Discrete Distributions Free7 Lesson 33 Min
- Continuous Distributions Free8 Lesson 41 Min
- Probability in Other Fields Free3 Lesson 18 Min
“Having a probabilistic mindset is much more important than knowing “absolute truths”, if you want to succeed in data science. I have carefully crafted this course to reflect the most in-demand skills that will enable you to understand and compute complex probabilistic concepts. This is the place where you’ll take your skillset to the next level – that of probability, conditional probability, Bayesian probability, and probability distributions.”
Content Creator at 365 Data Science
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