Introduction to Genetic Algorithms: Theory and Applications
What you will learn
Use the Genetic Algorithm to solve optimization problems
Modify or improve the Genetic Algorithm
Analyze the performance of the Genetic Algorithm
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Comidoc Review
Our Verdict
This course, "Introduction to Genetic Algorithms: Theory and Applications," ranks high with a rating of 4.54 out of 5 from over 4700 subscribers. The strengths of this course lie in its engaging instructor, Dr. Seyedali Mirjalili, and his ability to explain complex genetic algorithms' mechanisms systematically while combining both intuitive and rigorous explanations. Students find the real-time explanations and hiccups informative and clear, adding value even with an accent. The main weaknesses include requests for more detailed code explanations, fundamental MATLAB concept introductions, and improved video quality to eliminate coding mistakes. With these in mind, students looking for a hands-on, engaging experience with Genetic Algorithms should try this course—just be prepared for a non-traditional presentation approach and some self-study when it comes to the code.
What We Liked
- The course stands out with its systematic and thorough approach, combining both intuitive and rigorous explanations.
- Dr. Seyedali Mirjalili's engaging teaching style has been praised for his clarity and accessibility, making complex concepts easy to understand.
- This course offers real-world problem-solving with Genetic Algorithms, demonstrating its practical applications.
- Students also appreciate the inclusion of actual Matlab code that they can test, play, and learn from.
Potential Drawbacks
- Several students have noted slight difficulties due to Dr. Mirjalili's accent and informal presentation style.
- There were requests for deeper explanations of specific code sections, as well as an introduction to fundamental MATLAB concepts.
- A few students faced difficulties with video errors and coding mistakes that could hinder learning progress.