 
 A genetic algorithm (GA) is a metaheuristic inspired by natural selection that belongs to the broader class of evolutionary algorithms in computer science and operations research (EA). Genetic algorithms rely on biologically inspired operators like mutation, crossover, and selection to produce high-quality solutions to optimization and search problems.
Easy solutions to complex issues demonstrate the potential of genetic algorithms.
Use Elixir capabilities to write succinct genetic algorithms.
Learn how to use genetic algorithms to solve a problem from start to finish.
Learn how to solve a variety of problems using various methods and fine-tuning.
With application scenarios, you can plan, research, evaluate, and simulate your genetic algorithms.

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Hours 300
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