Probability And Distribution With Solved Problems By Spotle

Learn probability and distribution explained in detail with solved problems and exercises

What you'll learn
Learn probability, conditional probability, Bayes' theorem, and basic distribution explained through detailed videos
Learn random variables - continuous and discrete variables
Learn how to solve probability problems
Learn through exercises and solved problems
Requirements
In this Spotle compact course you will start from scratch
Description
One of the most talked about career options today is a career in Data Science. In this Spotle compact course we focus on building the foundation solid. To become a data scientist or a machine learning expert, it is essential to learn the concepts of probability. You need to be ready to apply the concepts in real-life problem solving. The concepts will be quite frequently applied in almost all areas of Data Science and Machine Learning.Probability, random variables, and probability distributions form the foundation of building complex algorithms.This course is also highly recommended for the students of standard 12 to graduation level who are dong major in Statistics, mathematics or in any tech based course such as biotech. Each and every topic in this Spotle compact course has been explained with multiple examples.At the end 30 problems have been explained in detail and solved. 20 exercises have been added to help you check that you have understood the topics very well. Practice as much as you can.In all Spotle compact courses we have created the videos so that you will need minimum time to learn, so that you can give more time to applying them in real-life.

Overview

Section 1: Introduction

Lecture 1 The Probability Concepts

Lecture 2 The Conditional Probability Concepts

Section 2: Conditional Probability

Lecture 3 Conditional Probability

Lecture 4 Bayes Theorem And Conditional Probability

Section 3: Random Variables

Lecture 5 What Is A Random Variable

Lecture 6 Random Variables - An Exercise

Lecture 7 Types Of Random Variables

Section 4: Probability Distribution

Lecture 8 Probability Mass And Density Function

Lecture 9 Uniform Distribution And Cumulative Distribution Function

Section 5: Expectations And Variance

Lecture 10 Calculating Expectations

Lecture 11 Calculating Variance

Section 6: Probability Distribution With Python

Lecture 12 Probability Distribution With Python

Section 7: Data Science/ Machine Learning Applications

Lecture 13 Naïve Bayes Classifier

Section 8: Solved Problems

Lecture 14 Probability Quiz - 10 Solved Problems With Detailed Explanation

Lecture 15 The Tricky Probability Test - 10 Solved Problems

Lecture 16 Random Variables And Distribution - 10 Solved Problems

Section 9: Exercise - 20 Problems On Probability And Permutation

Lecture 17 Exercise - 20 Problems On Probability And Permutation

This is an ideal course for the people who want to build a rewarding career in Data Science.,This course is highly recommended for the students of standard 12 to graduation level who are dong major in science.,This course helps learn probability concepts needed pretty much for any tech based course.

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