Probability for Data Science
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4.47
Beginner
2.25 Hrs
53.4K+
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About this course
The Probability for Data Science course begins with introducing you to different concepts in probability. It then continues with inculcating in you the skills to work with marginal probability to solve problems that are events irrespective of the outcome of another value and the Bayes Theorem that deals with the probability of occurrence of events based on the occurrence of other events. You can refer to the attached study materials at any point after enrolling in the course and take up the quiz at the end to test your knowledge and understand your gains. After completing this free, self-paced, beginner's guide to Probability for Data Science, you can register for top-rated Data Science Courses and embark on your Data Science career with a professional Post Graduate certificate and learn various concepts with millions of aspirants across the globe!
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Course Outline
Basics of Probability
This section includes answers to questions like what is probability? Why is there a need to learn probability? What are the rules of probability? You shall look at the application of probability later in this section.
Marginal Probability
You will learn about marginal probability and understand its features. The section also solves a problem when the condition is a margin to help you understand the concept better.
Bayes Theorem
The section begins with explaining what Bayes theorem is and then continues with helping you understand the concept with addition and multiplication rules. You will then work with a problem statement and derive a solution to it to understand the concept better.
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