This course covers the fundamentals of probability, including concepts such as expected values, frequency distribution, complement, combinatorics, conditional probability, and various types of probability distributions like binomial, Poisson, normal, and chi-squared distributions. The course aims to teach students the basic principles of probability and how to apply them in data science and statistics. The intended audience for this course includes beginners in data science, statistics enthusiasts, and anyone looking to enhance their understanding of probability concepts. The teaching method involves theoretical explanations, practical examples, and tutorials to help students grasp the concepts effectively.
Overview
Syllabus
What is probability | Expected Values, Frequency Distribution, Complement.
Combinatorics: Factorials Explained.
Probability: Intersection and Union of Sets.
Probability and Statistics: Conditional Probability.
Introduction to Probability Distributions.
Probability: Types of Distributions.
Introduction to Discrete Uniform Distribution.
Probability: Binomial Distribution.
Bernoulli Distribution.
Data Science & Statistics Tutorial: The Poisson Distribution.
Understanding the Normal Distribution [Statistics Tutorial].
Standard Normal Distribution.
Introduction to Probability: Student's T Distribution.
Data Science & Statistics: Chi-Squared Distribution.
Introduction to Probability | 365 Data Science Online Course.
Taught by
365 Data Science
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