Introduction To Applied Probability
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
-
Shilank Singh
Maths & Stats Tutor
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
- Top 10 Mobile App Development Courses to Learn in December 2024
- Top 10 Graphic Design Courses to Learn in December 2024
- Top 10 Videography Courses to Learn in December 2024
- Top 10 Photography Courses to Learn in December 2024
- Top 10 Language Learning Courses to Learn in December 2024
- Top 10 Product Management Courses to Learn in December 2024
- Top 10 Investing Courses to Learn in December 2024
- Top 10 Personal Finance Courses to Learn in December 2024
- Top 10 Health And Wellness Courses to Learn in December 2024
- Top 10 Chatgpt And Ai Tools Courses to Learn in December 2024
- Top 10 Virtual Reality Courses to Learn in December 2024
- Top 10 Augmented Reality Courses to Learn in December 2024
- Top 10 Blockchain Development Courses to Learn in December 2024
- Top 10 Unity Game Development Courses to Learn in December 2024
- Top 10 Artificial Intelligence Courses to Learn in December 2024
- Top 10 Flutter Development Courses to Learn in December 2024
- Top 10 Docker Kubernetes Courses to Learn in December 2024
- Top 10 Business Analytics Courses to Learn in December 2024
- Top 10 Excel Vba Courses to Learn in December 2024
- Top 10 Devops Courses to Learn in December 2024