Join 3 million developers at
Join 3 million developers at
LEARNING OBJECTIVES
- Get introduced to different solvers and algorithms for optimization
- Solve real-world linear optimization examples
- Learn how to use the PuLP library for linear optimization
Learning Roadmap
Introduction to Linear Programming and OptimizationReal-life Examples of Linear Programming in PythonIntroduction to Python and PuLPLinear Programming AlgorithmsSolvers in PuLPProblem: Maximizing Car Sales Profits Using PuLPQuiz: Linear Programming, Python, and PuLPProblem: Solving Sudoku Using PuLP, Part IProblem: Solving Sudoku Using PuLP, Part IIProblem: Balancing Chemical Equations, Part IProblem: Balancing Chemical Equations, Part IIQuizCongratulations!
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ABOUT THIS COURSE
We make optimization decisions every day. To improve the performance of your applications, computers need to do the same. This course will help you optimize computing functions through the open-source Python library PuLP.
In this course, you’ll learn about linear programming, an optimization approach that maximizes or minimizes functions through defined algebra, and the PuLP library along with its various optimizers available via APIs. You’ll identify the variables and constraints of computing functions and define the optimization goals. You’ll then learn and practice common linear programming algorithms. Finally, you’ll be introduced to potential applications in the real world.
By the end of the course, you will be able to optimize computing functions using Python and PuLP.
ABOUT THE AUTHOR
Rahul Banerjee
Energetic and passionate 4th-year Computer Engineering student with experience in working in an Agile environment. Experienced in React, Flask, JavaScript, and SQL.
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