Learn to solve optimization problems in Python using essential math tools, metaheuristic methods, and constrained optimization techniques. Master efficient solutions for real-world applications.
Beginner
50 Lessons
12h
Certificate of Completion
Learn to solve optimization problems in Python using essential math tools, metaheuristic methods, and constrained optimization techniques. Master efficient solutions for real-world applications.
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This course includes
This course includes
Course Overview
Optimization theory seeks the best solution, which is pivotal for machine learning, cost-cutting in manufacturing, refining logistics, and boosting finance profits. This course provides a detailed description of different optimization problems and the techniques used to solve them. You’ll begin with the formal definition of an optimization problem and an overview of essential mathematical tools: derivatives, gradients, and Hessian. With this knowledge, you’ll implement solutions for several optimization pr...Show More
What You'll Learn
An understanding of the mathematical foundations of optimization methods
Familiarity with population-based metaheuristic optimization methods such as genetic algorithms and particle swarm optimization
Hands-on experience in formulating, implementing, and solving optimization problems using Python
A working knowledge of Python libraries such as SciPy, NumPy, and CVXPY for solving optimization problems
What You'll Learn
An understanding of the mathematical foundations of optimization methods
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Course Content
Introduction
Derivatives and Gradients
First Optimization Algorithms
Population Methods
Adding Constraints
Solving Sudoku and the 8-Queens Puzzle as Constraint Satisfaction
Project
Linear Constrained Optimization
7 Lessons
Summary and Conclusion
2 Lessons
Appendix
1 Lesson
Maze Solver Using the Ant Colony Optimization Algorithm
Project
Course Author
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