Probability for Risk Management and Optimization

Probability for Risk Management and Optimization, available at $94.99, has an average rating of 4.3, with 47 lectures, 2 quizzes, based on 181 reviews, and has 572 subscribers.

You will learn about Basic application oriented Probability concepts. First step towards use of Probability concepts in Optimization. Probability and sensitivity applied in Risk Management Common source of conceptual mistakes related to Probability theory application. To model the Probabilistic situations with greater ease. Sharpen the learning without focusing on probability formulas. This course is ideal for individuals who are Those who wish to take advantage of probability concepts in their activities or Those who are excited about understanding nuances of Probability or Students studying Probability for any purpose or Students or professionals needing to learn probability concepts in risk management It is particularly useful for Those who wish to take advantage of probability concepts in their activities or Those who are excited about understanding nuances of Probability or Students studying Probability for any purpose or Students or professionals needing to learn probability concepts in risk management.

Enroll now: Probability for Risk Management and Optimization

Summary

Title: Probability for Risk Management and Optimization

Price: $94.99

Average Rating: 4.3

Number of Lectures: 47

Number of Quizzes: 2

Number of Published Lectures: 47

Number of Published Quizzes: 2

Number of Curriculum Items: 49

Number of Published Curriculum Objects: 49

Original Price: ₹3,999

Quality Status: approved

Status: Live

What You Will Learn

Basic application oriented Probability concepts.
First step towards use of Probability concepts in Optimization.
Probability and sensitivity applied in Risk Management
Common source of conceptual mistakes related to Probability theory application.
To model the Probabilistic situations with greater ease.
Sharpen the learning without focusing on probability formulas.

Who Should Attend

Those who wish to take advantage of probability concepts in their activities
Those who are excited about understanding nuances of Probability
Students studying Probability for any purpose
Students or professionals needing to learn probability concepts in risk management

Target Audiences

Those who wish to take advantage of probability concepts in their activities
Those who are excited about understanding nuances of Probability
Students studying Probability for any purpose
Students or professionals needing to learn probability concepts in risk management

Probability is a measure of uncertainty and we have to deal with it everywhere. Managing risk and optimizing system performance in uncertain situations are some of the major challenges faced by every professionals. This course discusses about probability and it’s sensitivity to help in risk management. It also gets into some kind of modelling to gain important insight into queue optimization. There are several application oriented practice questions with solutions in this course.

This course starts with basic probability concepts and focusses on first principles to build understanding about permutation, combination and counting. It discusses about some of the most popular probability distributions with an objective of moving towards application of the concepts. One should be able to improvise on these concepts to take care of special needs.

It works on some of the important concepts related to probability where students generally go wrong such as probability with continuous variables and not equally likely outcomes.

This course is not a conventional probability course discussing about various laws of probability and formulas to calculate probability values. But, it tries to make you understand the nuances of probability concepts so that you can become more comfortable in applying them and avoiding some of the serious mistakes.

Course Curriculum

Chapter 1: Warm-up

Chapter 2: Introduction

Lecture 1: Introduction

Lecture 2: Understanding Uncertainty and Probability

Lecture 3: Deterministic and Probabilistic Situations

Lecture 4: Subjective, Relative and Theoretical Probabilities

Lecture 5: Probability

Lecture 6: Conditional Probability

Chapter 3: Permutation, Combination and Counting

Lecture 1: Permutation

Lecture 2: Combination

Lecture 3: Probability Question 1

Lecture 4: Probability Question 2

Lecture 5: Probability Question 3

Chapter 4: Take Care

Lecture 1: Not Equally Likely Events

Lecture 2: Discrete Vs. Continuous

Lecture 3: Probability with Continuous Variable

Lecture 4: Probability Distribution

Lecture 5: Dependence on Previous Outcomes

Chapter 5: Binomial Distribution

Lecture 1: Binomial Distribution Build-up

Lecture 2: Binomial Distribution Application – 1

Lecture 3: Binomial Distribution Application – 2

Lecture 4: Few Questions for Smart Thinking on Binomial Distribution

Lecture 5: Binomial or Something Else

Chapter 6: Normal Distribution

Lecture 1: Normal Distribution Concept

Lecture 2: Normal Distribution Table

Lecture 3: Normal Distribution Inverse – Application in Project Planning

Chapter 7: Poisson Distribution in Queue Optimization

Lecture 1: Behavior of System in Small Time

Lecture 2: Possibilities Near Idle System State

Lecture 3: Possibilities for Any Other System State

Lecture 4: Probability of System Being in Any State

Lecture 5: Expected Length of The System

Lecture 6: Probabilities of Conflicting States

Lecture 7: Planning Service Rate and Facilities

Lecture 8: Waiting Time Consideration

Chapter 8: Probability Concepts in Risk Management

Lecture 1: Probability as Measure of Risk

Lecture 2: Computing Probability to Measure Risk

Lecture 3: Risk Zones

Lecture 4: Sensitivity of Probability

Lecture 5: Expected Value in Decision Making

Chapter 9: Miscellaneous Probability Problems

Lecture 1: Answers of Practice Questions A (Counting, Probability and Data)

Lecture 2: Practice Questions B (4 questions on Probability and Data Requirement)

Lecture 3: Answers of Practice Questions B

Lecture 4: Answers of Practice Questions C

Lecture 5: Answers of Practice Questions D

Lecture 6: Answers of Practice Question E

Lecture 7: Answers of Practice Questions F (Normal Distribution – No Computation)

Lecture 8: Answers of Practice Questions G (Normal Distribution Probability Computation)

Lecture 9: Answers of Practice Questions H (Queue Optimization)

Lecture 10: Some Teasing Questions on Basic Probability Concept

Instructors

Girijesh Pathak
Experienced Faculty, Tech Head and Operations Head

Rating Distribution

1 stars: 2 votes
2 stars: 1 votes
3 stars: 14 votes
4 stars: 59 votes
5 stars: 105 votes

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