Optimization with Python: Complete Pyomo Bootcamp AZ Optimization with Python: Complete Pyomo Bootcamp AZ course published by Udemy Academy. Teaching how to use CPLEX, IPOPT, and COUENNE solvers to solve linear, non-linear and integer programming problems in Python
Mathematical optimization is becoming more and more popular in most quantitative disciplines such as engineering, management, economics, and operational research. In addition, Python is one of the most famous programming languages that has received more attention today. Therefore, we decided to create a course to master the development of optimization problems in the Python environment.
In this course, you will learn how to deal with different types of mathematical optimization problems. Since this course is designed for all levels (beginner to advanced), we start from scratch where you have to formulate a problem. Therefore, after completing this course, you will be able to find and formulate decision variables, objective function, constraints and define your parameters. In addition, you will learn how to develop the formulated model in the Python environment (using the Pyomo package).
What you will learn in the course Optimization with Python: Complete Pyomo Bootcamp AZ:
- Basic concepts and terms related to optimization
- How to formulate a math problem.
- Linear programming and LP programming problems in Python using Pyomo
- Mixed Integer Linear Programming (MILP) and coding MILP problems in Python using Pyomo
- Non-linear programming (NLP) and coding NLP problems in Python using Pyomo
- Mixed Integer Nonlinear Programming (MINLP) and coding MINLP problems in Python using Pyomo
Who is this course suitable for:
- Students in all levels (bachelor’s, master’s and doctorate)
- Companies that want to use optimization in their business.
- Specialists in various fields such as engineering, management and operational research
- Anyone interested in learning optimization and coding in Python!
Optimization with Python Course details
- Publisher: Udemy
- Instructor: Navid Shirzadi
- English language
- Training level: introductory to advanced
- Number of courses: 38
- Training duration: 9 hours and 24 minutes
Optimization with Python Course headings
Optimization with Python Course prerequisites
General and Basic Python Skills
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