Optimization problems and algorithms [2024]
What you'll learn
- Identify, understand, formulate, and solve optimization problems
- Understand the concepts of stochastic optimization algorithms
- Analyse and adapt modern optimization algorithms
- Understand the process of optimizing and solving an optimization problem
Requirements
- You should have basic knowledge of programming
- You should be familiar with Matlab's built-in programming language
Description
This introductory course dives into stochastic optimization problems and algorithms, fundamental sub-fields in Artificial Intelligence. You'll cover essential concepts, including metaheuristics and swarm intelligence, and learn to identify and implement key components of optimization problems.
Why Enroll in This Course?
Foundational Knowledge: Learn the basics of optimization, including constraints, multiple objectives, discrete variables, and uncertainties.
Hands-On Coding: Follow step-by-step coding videos to implement optimization algorithms and solve real-world problems in Matlab.
Practical Exercises: Reinforce your learning with quizzes and exercises designed to test your understanding.
What You'll Learn:
History of Optimization: Discover the evolution of optimization techniques and their applications.
Optimization Problems: Understand different types of optimization problems and their challenges.
Single-Objective Optimization Algorithms: Learn to solve problems focused on a single objective.
Particle Swarm Optimization (PSO): Master PSO, a versatile algorithm applicable to Machine Learning, Data Science, Neural Networks, and Deep Learning.
Advanced Optimization Techniques: Tackle problems with constraints, binary/discrete variables, multiple objectives, and uncertainties.
Course Highlights:
Comprehensive Curriculum: Covering both theoretical concepts and practical applications.
Interactive Learning: Coding videos, quizzes, and exercises to practice and reinforce your knowledge.
Expert Instruction: Learn from Prof. Seyedali Mirjalili, a leading researcher in optimization and AI with over 500 publications and 110,000 citations globally.
Student Testimonials:
David: "This course is one of the best online courses I have ever taken. The instructor did an excellent job preparing the content and explains the complicated code very carefully."
Khaled: "Dr. Seyedali is one of the greatest instructors. The course is direct and comprehensive, making optimization and PSO easy to understand. Highly recommended!"
Biswajit: "This course has been very helpful. The emphasis on coding and visualization of results is outstanding. The support provided by Dr. Seyedali is top-notch."
Boumaza: "A clear picture of optimization algorithms, covering both technical and practical aspects. Step-by-step and practical approach to optimization. Highly recommended!"
Join Over 5000+ Students:
Start your optimization journey with us today! If you're not satisfied for any reason, Udemy offers a full refund within 30 days—no questions asked. But we're confident you'll find this course invaluable.
Enroll Now and master optimization problems and algorithms with expert guidance.
Who this course is for:
- Anyone who wants to learn optimization
- Anyone who wants to solve an optimization problem
- Anyone who wants to have an in-depth understanding of optimization
Featured review
Instructor
- 4.5 Instructor Rating
- 5,326 Reviews
- 21,369 Students
- 8 Courses
Professor Seyedali (Ali) Mirjalili is internationally recognized for his advances in Artificial Intelligence (AI) and optimization, including the first set of SI techniques from a synthetic intelligence standpoint - a radical departure from how natural systems are typically understood - and a systematic design framework to reliably benchmark, evaluate, and propose computationally cheap robust optimization algorithms. Prof. Mirjalili has published over 500 research outputs.
Prof. Mirjalili has over 110,000 citations in total with an H-index of 110. From Google Scholar metrics, he is globally one of the most-cited researchers in Artificial Intelligence. As the most cited researcher in Robust Optimization, he is in the list of 1% highly-cited researchers and named as one of the most influential researchers in AI by the world by Web of Science. In 2022 and 2023, The Australian newspaper recognized him as a global leader in Artificial Intelligence and a national leader in the Evolutionary Computation and Fuzzy Systems fields.
Ali is a senior member of IEEE and an associate editor of several journals including IEEE Access, Applied Soft Computing, Advances in Engineering Software, and Applied Intelligence. His research interests include Robust Optimization, Engineering Optimization, Multi-objective Optimization, Swarm Intelligence, Evolutionary Algorithms, and Artificial Neural Networks. He is working on the application of multi-objective and robust meta-heuristic optimization techniques as well.
In addition to his excellent research outputs, Prof. Ali has been a teacher for over 15 years and a Udemy instructor for more than three years. He has 10,000+ students, and the majority of his courses have been highly ranked by both Udemy and students. He is the only Udemy instructor in the list of top 1% highly-cited researchers.