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Linear Programming basics

Learn the simplex method, duality and sensitivity analysis for linear programs
5.0
5.0/5
(1 reviews)
4 students
Created by

9.9

CourseMarks Score®

10.0

Freshness

10.0

Feedback

9.1

Content

Platform: Udemy
Video: 3h 6m
Language: English
Next start: On Demand

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Detailed Analysis

CourseMarks Score®

9.9 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 5/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

10.0 / 10
We analyzed factors such as the rating (5.0/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.1 / 10
Video Score: 8.0 / 10
The course includes 3h 6m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
Detail Score: 9.3 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

4 articles.
4 resources.
0 exercise.
0 test.

Table of contents

Description

Linear programming is a widely used optimization tool in various application (data science, engineering, transportation, supply chain, etc.). Linear programming also makes the basic  foundation behind complex optimization tools like Mixed Integer Liner Programming (MILP) and Column generation. In this course, we will study the basic theoretical concepts related to linear programming.

The course is organized as follows. In the first section, we will introduce linear programming, and we will explore the convexity and types of optimalities. Then, in the second section, we will build up on the basics to learn ways to solve the linear program using simplex method. We will then explore the concept of linear programming duality. We will also go through some of the hardest to understand concepts like strong duality, complementary slackness and Farkas’ lemma. Furthermore, we try to understand these concepts in an easy-to-follow way. This allows one to obtain lower bounds on the minimization problem and provide a proof of optimality or Infeasibility. In the last section, we will explore how to perform sensitivity analysis (the effects of changing parts of a linear program). At the end of each section, there are assignments to help you evaluate your knowledge.

As you would have noticed, this course doesn’t explore modeling optimization problems as a linear program much. That is a separate topic and deserves an entire course on it.

You will learn

✓ Describe what a linear program is.
✓ Solve a linear program using graphical and simplex methods.
✓ Compute the dual of the given linear program.
✓ Use the primal and dual values to prove optimality or infeasibility of the given linear program..
✓ Compute how the solution value changes under minor modification of the given linear program.

Requirements

• Basic knowledge of linear algebra is required to understand various proofs presented.
• No programming experience needed.

This course is for

• Students and professionals working with optimization and artificial intelligence.

How much does the Linear Programming basics course cost? Is it worth it?

The course costs $14.99. And currently there is a 67% discount on the original price of the course, which was $22. So you save $7 if you enroll the course now.

Does the Linear Programming basics course have a money back guarantee or refund policy?

YES, Linear Programming basics has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Linear Programming basics course, but there is a $7 discount from the original price ($22). So the current price is just $14.99.

Who is the instructor? Is Krunal Patel a SCAM or a TRUSTED instructor?

Krunal Patel has created 1 courses that got reviews which are generally positive. Krunal Patel has taught 4 students and received a 5.0 average review out of reviews. Depending on the information available, Krunal Patel is a TRUSTED instructor.
Ex Googler and PhD Student at Polytechnique Montreal
I graduated from BITS Pilani Goa Campus in 2015 with B. E. (Hons.) Computer Science and M. Sc. (Hons.) Mathematics. After graduation, I worked with Google from 2015 to 2020 with operations research team. With the operations research team I worked as a developer of Google OR-Tools. I Left Google in 2020 to start my PhD under the supervision of Prof. Andrea Lodi and Prof. Guy Desaulniers in applied mathematics.

My research interests:
Discrete optimization
Column Generation
Machine Learning.

9.9

CourseMarks Score®

10.0

Freshness

10.0

Feedback

9.1

Content

Platform: Udemy
Video: 3h 6m
Language: English
Next start: On Demand

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