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If you’re interested in solving large-scale optimization problems using advanced search techniques, the Udemy course ‘Python ile Genetik Algoritma’ is an excellent choice. This course delves into the world of meta-heuristic algorithms, focusing on Genetic Algorithms (GA), which mimic biological evolution to find optimal solutions. The instructor guides learners through the fundamental concepts, such as population dynamics, selection, crossover, mutation, and elitism, providing a solid theoretical foundation.
What sets this course apart is its practical approach. It not only explains the underlying theory but also demonstrates how to implement GA in Python using real-world examples like the Traveling Salesman Problem (TSP) and Quadratic Assignment Problem (QAP) from renowned libraries such as TSPLIB and QAPLIB. Students get hands-on experience in coding, analyzing results, visualizing solutions, and optimizing performance.
Designed for those with basic knowledge of Operations Research, combinatorial optimization, and Python programming, this course makes complex topics accessible. The instructor ensures that even beginners can follow along and understand the concepts thoroughly.
I highly recommend this course for anyone wanting to deepen their understanding of genetic algorithms and enhance their problem-solving toolkit with Python. Whether you’re a student, researcher, or professional, this course is a valuable resource to master meta-heuristics and practical optimization techniques.
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