How to understand, formulate, and tackle the difficulties of optimization problems using heuristic algorithms in Matlab by downloading the Optimization problems and algorithms udemy course.
What you'll learn
- Identify, understand, formulate, and solve optimization problems
- Understand the concepts of stochastic optimization algorithms
- Analyse and adapt modern optimization algorithms
- You should have basic knowledge of programming
- You should be familiar with Matlab's built-in programming language
This is an introductory Optimization problem and algorithms course to the stochastic optimization problems and algorithms as the basics sub-fields in Artificial Intelligence. We will cover the most basic concepts in the field of optimization including metaheuristics and swarm intelligence. By the end of this Optimization problems and algorithms course, you will have the ability to recognize and implement the primary parts of an optimization problem. Optimization problems are different, yet there have mostly similar challenges and problems such as restraints, several goals, discrete variables, and sounds. This course will show you how to take on each of these troubles. Most of the lectures come with coding videos. In such videos, the step-by-step procedure of implementing the optimization algorithms or problems exist. We have also a number of quizzes and exercises to practice the theoretical knowledge covered in the lectures.
Here is the list of topics covered:
- History of optimization
- Optimization problems
- Single-objective optimization algorithms
- Particle Swarm Optimization
- Optimization of problems with constraints
- Optimization of problems with binary and/or discrete variables
- Optimization of problems with multiple goals
- Optimization of problems with unpredictabilities
Particle Swarm Optimization will be the primary algorithm, which is a search technique that can be easily applied to various applications consisting of Machine Learning, Data Science, Neural Networks, and Deep Learning.
I am proud of 200+ 5-star evaluations. A few of the reviews are as follows:
David said: “This Optimization problems and algorithms course is among the very best online course I have ever taken. The instructor did an outstanding job to very thoroughly prepare the contents, slides, videos, and discusses the complex code in a really mindful method. I hope the instructor can develop many more courses to enhance society. Thanks!”
Khaled stated: “Dr. Seyedali is among the best trainer that i had the opportunity to take a course with. The course was direct to the point and the lessons are easy to understand and comprehensive. He is extremely helpful throughout and out of the course. i really suggest this course to all who wish to learn optimization \ PSO or those who wish to sharpen their understanding of optimization. finest of luck to all and THANK YOU Dr. Seyedali.”
Biswajit stated: “This coursework has really been really helpful for me as I have to frequently handle optimization. The most prominent function of the course is the focus given on coding and visualization of results. Even more, the assistance offered by Dr. Seyedali through personal interaction is top-notch.
Boumaza stated: “Good Course from Dr. Seyedali Mirjalili. It offers us a clear photo of the algorithms utilized in optimization. It covers technical along with useful elements of optimization. Step by step and really useful method to optimization through well though and effectively discussed subjects, extremely recommended course You really help me a lot. I hope, sooner or later, I will be one of the gamers in this interesting field! Thanks to Dr. Seyedali Mirjalili.”
Join 1000+ trainees and begin your optimization journey with us. If you are in any way not pleased, for any reason, you can get a full refund from Udemy within 30 days. No questions asked. However, I am confident you will not require to. I stand behind this course 100% and am committed to assisting you along the way.
Who this course is for:
- Anybody who wishes to discover optimization
- Anyone who wishes to resolve an optimization problem