Enroll Course: https://www.udemy.com/course/mathematical-optimization-with-gams-and-pyomo-python/
If you’re interested in mastering the fundamentals of optimization in engineering, science, or management, the ‘Mathematical Optimization with GAMS and Pyomo (Python)’ course on Udemy is an excellent starting point. This course provides a well-structured introduction to various types of optimization problems, including Linear Programming, Nonlinear Programming, Mixed Integer Linear Programming, and Mixed-Integer Nonlinear Programming.
The course is divided into four informative modules, each featuring three illustrative examples and an assignment from different fields. This hands-on approach ensures that learners can see practical applications of the concepts learned, whether in scientific research, engineering design, or business decision-making.
One of the highlights of this course is its focus on coding in two widely-used environments: GAMS and Pyomo (Python). GAMS, a licensed optimization software, is introduced using a demo license, while Pyomo, an open-source Python package, is demonstrated via Google Colaboratory, making it accessible to all learners. Throughout the course, you’ll learn how to import and export data, define and manipulate variables, and solve complex optimization problems with different solvers, including the NEOS server.
By the end of this course, you’ll be equipped with the skills to read problem statements, build models, and code in both GAMS and Pyomo. Whether you’re a student, researcher, or professional, this course offers a solid foundation in optimization techniques with practical coding skills that can be directly applied to real-world problems.
Overall, I highly recommend this course for anyone looking to deepen their understanding of optimization methods and improve their modeling and coding skills in GAMS and Python. It’s a perfect blend of theory and practical application, making complex concepts accessible and engaging.
Enroll Course: https://www.udemy.com/course/mathematical-optimization-with-gams-and-pyomo-python/