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Linear Programming With Python - AD-TEAM - 10-26-2025
![[Image: 284dc396fc1f5ce4c95755a39f3b5c39.jpg]](https://i126.fastpic.org/big/2025/1026/39/284dc396fc1f5ce4c95755a39f3b5c39.jpg)
Linear Programming With Python
Published 9/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 678.07 MB | Duration: 1h 52m
Learn linear programming step by step with Python - build models, solve optimization problems, and apply in real cases.
What you'll learn
Formulate real-world problems as linear programming models
Write objective functions and constraints in mathematical form
Implement and solve optimization models using Python libraries
Interpret solutions and apply results to decision-making scenarios
Requirements
No prior experience in optimization is required. Basic Python knowledge is helpful but not mandatory, as all steps are explained in detail.
Description
This course is designed to teach you linear programming from the ground up, using Python as a practical tool to model and solve optimization problems. Whether you are a student, an engineer, or someone interested in decision science, you will find clear explanations and hands-on coding examples that connect theory to application.We begin with the fundamentals: what linear programming is, how objective functions and constraints work, and why these models are so widely used in industries such as logistics, manufacturing, and operations management. Each concept is explained in plain language, and mathematical expressions are read out naturally, for example, 'three x plus two y is less than or equal to one hundred.'After understanding the basics, you will move into Python implementation. We use libraries that make it easy to define and solve optimization problems. You will learn how to translate a real situation into a mathematical model, write it in Python, and interpret the solution. Along the way, we will address common mistakes and clarify points that usually confuse beginners.By the end of this course, you will have the ability to set up your own optimization models, test them with data, and use Python to find the best solutions. The skills you gain here are practical, transferable, and highly useful for anyone interested in optimization and applied problem solving.
Overview
Section 1: Introduction
Lecture 1 Intro
Section 2: What is Linear Programming?
Lecture 2 Introduction to LP
Section 3: Linear Algebra Basics
Lecture 3 Matrix Operations
Lecture 4 Determinant Calculations
Lecture 5 Matrix Inverse
Lecture 6 Linear Equation Systems
Section 4: Linear Programming Examples in Python
Lecture 7 Problem Formulation
Lecture 8 Standard Form Conversion
Lecture 9 Graphical Method
Lecture 10 Simplex Algorithm
Lecture 11 Twoase Simplex
Lecture 12 Big M Method
Section 5: Linear Programming with Pyomo
Lecture 13 Bakery Optimization
Section 6: Linear Programming Recap
Lecture 14 Information About Simplex Lessons
Lecture 15 Intro to Linear Programming
Lecture 16 Formulating LP Problem
Lecture 17 Standard Form of LP
Lecture 18 Basic Example of LP
Lecture 19 Canonical Form of LP
Lecture 20 Fundamentals of the Simplex Method
Lecture 21 Steps - Simplex
Lecture 22 Manual Example - Simplex
This course is for students, engineers, analysts, and anyone curious about optimization and decision science. It is also suitable for Python learners who want to see how programming can be applied to solve real business and engineering problems.
![[Image: 52aoK2EE_o.jpg]](https://images2.imgbox.com/cf/30/52aoK2EE_o.jpg)
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