Udemy – The Ultimate Beginners Guide to Genetic Algorithms In Python 2022-2

Published on: 2022-12-28 03:39:16

Categories: 28

Description

The Ultimate Beginners Guide to Genetic Algorithms in Python published by Udemy Academy. Implementation of genetic algorithms from scratch to solve real world problems!

Genetic algorithms are an important area of artificial intelligence responsible for solving complex real-world problems. There are many practical applications of this type of algorithm that can be used to solve problems in everyday business situations. A classic example is solving the problem of scheduling teachers in schools, where there are different combinations of schedules and classes, and the goal is to build the schedule dynamically according to the number of classes and the availability of each teacher. Other examples are: telecommunication companies can design new optical networks, operators can better plan the route of goods delivery, investors can choose the best investment. Among several others

In this course, you will learn everything you need to enter the world of genetic algorithms! What makes this course unique is that you will learn basic intuition and especially step-by-step implementation without using pre-built libraries. In other words, we are going to implement genetic algorithms from scratch using Python. If you have never heard of this topic, at the end of the course you will have all the theoretical and practical foundations to solve your problems or the company you work for!

What you will learn in the The Ultimate Beginners Guide to Genetic Algorithms In Python course:

Learn the basic concepts of genetic algorithms in theory and practice, such as: individual, population, crossover/production, mutation and evaluation.
Implementation of genetic algorithms from scratch in Python.
Use genetic algorithms to maximize and minimize problems.
Visualize genetic algorithm results using dynamic graphs.
Integration of genetic algorithms with MySql database.
Learn how to build genetic algorithms using the DEAP and MLROSe libraries.
And …

Who is this course suitable for:

People interested in genetic algorithms, optimization algorithms or artificial intelligence
People who are interested in implementing genetic algorithms from scratch.
People interested in DEAP and MLROSe libraries
Students who are studying subjects related to artificial intelligence.
Data scientists who want to increase their knowledge in genetic algorithms.