This course introduces the foundations of optimization and shows how AI can be applied to real-world science and engineering optimization problems. You will learn about evolutionary computation, a branch of AI for optimization.
You will explore two widely used AI-based optimization techniques: genetic algorithms and particle swarm optimization. Along the way, you will learn how these methods work, when to use them, and how to implement them in MATLAB toolboxes to solve design and decision-making problems.
The course combines core concepts with practical science and engineering case studies, helping you move from theory to application. By the end of the course, you will be able to define optimization problems and use AI methods to obtain solutions in realistic contexts.
In partnership with MathWorks, enrolled learners receive access to MATLAB for the duration of the course.
Status: Engineering Design Process
Engineering Design Process
Status: Mathematical Modeling
Mathematical Modeling
Beginner·Course·9 hours
Featured reviews
5.0
·Reviewed Nov 20, 2025
The course’s emphasis on robustness and adaptability in evolutionary solutions has equipped me to handle noisy data and dynamic environments in real-time control systems.
5.0
·Reviewed Nov 20, 2025
The instructor’s expertise in evolutionary multi-objective optimization (EMO) helped me tackle complex trade-offs in sustainable urban planning projects.
5.0
·Reviewed Nov 9, 2025
Amazing lectures, I have learnt a lot. Many thanks.
5.0
·Reviewed Nov 21, 2025
The hands-on projects made mastering genetic algorithms feel effortless and immediately applicable to real-world engineering challenges.
5.0
·Reviewed Nov 20, 2025
The course’s comparison of evolutionary algorithms with traditional gradient-based methods highlighted their unique advantages in non-convex and high-dimensional problems.
5.0
·Reviewed Nov 20, 2025
This course demystifies evolutionary algorithms with clear explanations and practical examples, making complex optimization techniques accessible to all engineers and scientists.
5.0
·Reviewed Dec 1, 2025
The instructor’s expertise in genetic programming and evolutionary strategies brought real world relevance to abstract concepts like multi-objective optimization.
5.0
·Reviewed Dec 1, 2025
The comparison between traditional math optimization and evolutionary computation was eye opening. It clarified why AI methods are so powerful!
5.0
·Reviewed Nov 21, 2025
This course revolutionized my approach to complex optimization problems with practical evolutionary computation techniques.
5.0
·Reviewed Nov 9, 2025
Very excellent talk, really enjoyed the lecture!!!
5.0
·Reviewed Nov 23, 2025
Thanks to this course, I can now confidently use MATLAB to solve optimization problems with evolutionary algorithms. Practical skills that immediately paid off!
5.0
·Reviewed Nov 23, 2025
Finally, a course that explains why evolutionary algorithms work, not just how to use them. Deepened my understanding of AI’s engineering potential!
All reviews
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W
WenD
5.0
·Reviewed Nov 21, 2025
This course demystifies evolutionary algorithms with clear explanations and practical examples, making complex optimization techniques accessible to all engineers and scientists.
Z
Zhidrg
5.0
·Reviewed Nov 21, 2025
The course’s comparison of evolutionary algorithms with traditional gradient-based methods highlighted their unique advantages in non-convex and high-dimensional problems.
S
Suz
5.0
·Reviewed Nov 21, 2025
The course’s emphasis on robustness and adaptability in evolutionary solutions has equipped me to handle noisy data and dynamic environments in real-time control systems.
M
MaliF
5.0
·Reviewed Dec 1, 2025
The instructor’s expertise in genetic programming and evolutionary strategies brought real world relevance to abstract concepts like multi-objective optimization.
E
Ella
5.0
·Reviewed Nov 24, 2025
Thanks to this course, I can now confidently use MATLAB to solve optimization problems with evolutionary algorithms. Practical skills that immediately paid off!
T
triick
5.0
·Reviewed Nov 21, 2025
The instructor’s expertise in evolutionary multi-objective optimization (EMO) helped me tackle complex trade-offs in sustainable urban planning projects.
J
James
5.0
·Reviewed Nov 24, 2025
Finally, a course that explains why evolutionary algorithms work, not just how to use them. Deepened my understanding of AI’s engineering potential!
M
Mason
5.0
·Reviewed Dec 2, 2025
The comparison between traditional math optimization and evolutionary computation was eye opening. It clarified why AI methods are so powerful!
Z
Zhl
5.0
·Reviewed Nov 22, 2025
The hands-on projects made mastering genetic algorithms feel effortless and immediately applicable to real-world engineering challenges.
E
Ethan
5.0
·Reviewed Mar 14, 2026
The course has provided me with valuable theoretical and practical insights, which have been highly beneficial to my research topic.
O
Olivia
5.0
·Reviewed Nov 24, 2025
This course bridged the gap between theoretical AI and practical engineering. Every module had clear, actionable takeaways!
D
Dong
5.0
·Reviewed Nov 22, 2025
This course revolutionized my approach to complex optimization problems with practical evolutionary computation techniques.
L
Later
5.0
·Reviewed Dec 2, 2025
Great! This course is a must for anyone interested in nature inspired problem solving.
Q
Qiang
5.0
·Reviewed Nov 10, 2025
Amazing lectures, I have learnt a lot. Many thanks.
Q
Qing
5.0
·Reviewed Nov 10, 2025
Very excellent talk, really enjoyed the lecture!!!