HOT

Introduction To Applied Probability

Teaching & Academics

Rating3.8
Enroll Now

Introduction To Applied Probability, available at $34.99, has an average rating of 3.8, with 35 lectures, based on 27 reviews, and has 518 subscribers.

You will learn about Basic Definitions related to Probability Theory Mathematical Definition of Probability Important Symbols and Results related to Probability Theory Conditional Probability Theorem of Total Probability Baye's Theorem Bernoulli's Trials Probability of Uncountable Uniform Spaces This course is ideal for individuals who are Current Probability and Statistics students, or students about to start Probability and Statistics who are looking to get ahead or Students of Machine Learning, Data Science, Computer Science, Electrical Engineering , as Probability is the prerequisite course to Machine Learning, Data Science, Computer Science and Electrical Engineering or Anyone who wants to study Probability for fun after being away from school for a while. It is particularly useful for Current Probability and Statistics students, or students about to start Probability and Statistics who are looking to get ahead or Students of Machine Learning, Data Science, Computer Science, Electrical Engineering , as Probability is the prerequisite course to Machine Learning, Data Science, Computer Science and Electrical Engineering or Anyone who wants to study Probability for fun after being away from school for a while.

Enroll now: Introduction To Applied Probability

Summary

Title: Introduction To Applied Probability

Price: $34.99

Average Rating: 3.8

Number of Lectures: 35

Number of Published Lectures: 35

Number of Curriculum Items: 35

Number of Published Curriculum Objects: 35

Original Price: $94.99

Quality Status: approved

Status: Live

What You Will Learn

  • Basic Definitions related to Probability Theory
  • Mathematical Definition of Probability
  • Important Symbols and Results related to Probability Theory
  • Conditional Probability
  • Theorem of Total Probability
  • Baye's Theorem
  • Bernoulli's Trials
  • Probability of Uncountable Uniform Spaces

Who Should Attend

  • Current Probability and Statistics students, or students about to start Probability and Statistics who are looking to get ahead
  • Students of Machine Learning, Data Science, Computer Science, Electrical Engineering , as Probability is the prerequisite course to Machine Learning, Data Science, Computer Science and Electrical Engineering
  • Anyone who wants to study Probability for fun after being away from school for a while.

Target Audiences

  • Current Probability and Statistics students, or students about to start Probability and Statistics who are looking to get ahead
  • Students of Machine Learning, Data Science, Computer Science, Electrical Engineering , as Probability is the prerequisite course to Machine Learning, Data Science, Computer Science and Electrical Engineering
  • Anyone who wants to study Probability for fun after being away from school for a while.

HOW INTRODUCTION TO APPLIED PROBABILITY IS SET UP TO MAKE COMPLICATED PROBABILITY AND STATISTICS EASY

This course deals with concepts required for the study of Machine Learning and Data Science. Statistics is a branch of science that is an outgrowth of the Theory of Probability. Probability & Statistics are used in Machine Learning, Data Science, Computer Science and Electrical Engineering.

This 35+ lecture course includes video explanations of everything from Fundamental of Probability, and it includes more than 35+ examples (with detailed solutions) to help you test your understanding along the way. Introduction To Applied Probability is organized into the following sections:

  • Introduction

  • Some Basic Definitions

  • Mathematical Definition of Probability

  • Some Important Symbols

  • Important Results

  • Conditional Probability

  • Theorem of Total Probability

  • Baye’s Theorem

  • Bernoulli’s Trials

  • Uncountable Uniform Spaces

Course Curriculum

Chapter 1: Introduction

Lecture 1: Why do we need Probability

Chapter 2: Some Basic Definitions

Lecture 1: Some Basic Definitions – Part 1

Lecture 2: Some Basic Definitions – Part 2

Lecture 3: Some Basic Definitions – Part 3

Lecture 4: Some Basic Definitions – Part 4

Chapter 3: Mathematical Definition of Probability

Lecture 1: Probability – Definition and Solved Example 1, 2 and 3

Lecture 2: Probability – Definition and Solved Example 4

Lecture 3: Probability – Definition and Solved Example 5 and 6

Lecture 4: Probability – Definition and Solved Example 7

Chapter 4: Some Important Symbols

Lecture 1: Some Important Symbols

Chapter 5: Important Results

Lecture 1: Important Results – Concept and Solved Example 1

Lecture 2: Important Results – Solved Example 2

Lecture 3: Important Results – Solved Example 3

Lecture 4: Important Results – Solved Example 4

Lecture 5: Important Results – Solved Example 5 and 6

Lecture 6: Important Results – Solved Example 7

Chapter 6: Conditional Probability

Lecture 1: Conditional Probability – Concept and Solved Example 1

Lecture 2: Conditional Probability – Solved Example 2

Lecture 3: Conditional Probability – Solved Example 3

Chapter 7: Theorem of Total Probability

Lecture 1: Theorem of Total Probability – Concept and Solved Example 1

Lecture 2: Theorem of Total Probability – Solved Example 2

Lecture 3: Theorem of Total Probability – Solved Example 3

Lecture 4: Theorem of Total Probability – Solved Example 4

Chapter 8: Baye's Theorem

Lecture 1: Baye's Theorem – Concept and Solved Example 1

Lecture 2: Baye's Theorem – Solved Example 2

Lecture 3: Baye's Theorem – Solved Example 3

Lecture 4: Baye's Theorem – Solved Example 4

Chapter 9: Bernoulli's Trials

Lecture 1: Bernoulli's Trials – Concept and Solved Example 1 and 2

Lecture 2: Bernoulli's Trials – Solved Example 3

Lecture 3: Bernoulli's Trials – Solved Example 4

Lecture 4: Bernoulli's Trials – Solved Example 5

Lecture 5: Bernoulli's Trials – Solved Example 6

Lecture 6: Bernoulli's Trials Generalisation- Concept and Solved Example 1

Chapter 10: Uncountable Uniform Spaces

Lecture 1: Uncountable Uniform Spaces – Solved Example 1

Lecture 2: Uncountable Uniform Spaces – Solved Example 2

Instructors

Rating Distribution

  • 1 stars: 0 votes
  • 2 stars: 3 votes
  • 3 stars: 8 votes
  • 4 stars: 5 votes
  • 5 stars: 11 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

You may also like

Google Ads MasterClass – All Advanced Features

Video Marketing Masterclass

Pinterest Marketing from A to Z for Beginners