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Artificial Intelligence: Optimization Algorithms in Python

Learn how to build optimization algorithms from the ground up!
Rating: 4.5 out of 54.5 (34 ratings)
599 students
Created by Jones Granatyr, IA Expert Academy, Ligency Team
Last updated 8/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Learn the theory and implement optimization algorithms from scratch for solving real problems
  • Implement step by step the following algorithms in Python: random search, hill climb, simulated annealing, and genetic algorithms
  • Solve real problems for optimising flight calendars and dormitory room optimisation (limited resources)
  • Implement optimisation algorithms using predefined libraries

Requirements

  • Programming logic (if, while and for statements)
  • Basic Python programming
  • No prior knowledge about Artificial Intelligence

Description

What would an “optimal world” look like to you? Would people get along better? Would transport run faster? Would we take better care of our environment?

Many data scientists choose to optimize by using pre-built machine learning libraries.  But we think that this kind of 'plug-and-play' study hinders your learning. That's why this course gets you to build an optimization algorithm from the ground up.

In Artificial Intelligence: Optimization Algorithms in Python, you'll get to learn all the logic and math behind optimization algorithms. With two highly practical case studies, you'll also find out how to apply them to solve real-world problems.

In the first case study, we'll optimize travel plans for six friends who want to fly out from the same airport. In the second case study, we'll optimize the way university administrators allocate dorm rooms to new students.

On the way, we'll learn what optimization algorithms are. We'll find out how they can be applied to daily business practice. And we'll see how they can learn by themselves.

This course introduces you to four types of optimization algorithms:

- random search

- hill climb

- simulated annealing, and

- genetic

Don't worry if you're not yet sure what any of these are. We'll go through each one in detail, and you'll find out how to build each of them in our two case studies."

Who this course is for:

  • Beginners who are starting to learn about Artificial Intelligence
  • People interested in the theory of optimization algorithms
  • Undergraduate students who are studying subjects related to Artificial Intelligence
  • People interested in solving real problems using optimisation algorithms
  • Anyone interested in Artificial Intelligence

Course content

10 sections • 60 lectures • 6h 45m total length

  • Preview04:37
  • Preview05:43
  • Source code and slides
    00:16

  • Plan of attack
    01:53
  • Preview05:05
  • Creating the variables
    05:17
  • Flights dataset
    12:49
  • Printing the flights schedule - implementation
    13:41
  • Installing Anaconda and PyCharm
    06:57
  • Printing the flights schedule - debug
    09:51
  • Hours to minutes - implementation
    06:07
  • Fitness function - implementation 1
    11:41
  • Fitness function - implementation 2
    10:20
  • Preview16:04

  • Plan of attack
    01:43
  • Implementation
    15:59
  • Debug
    04:54

  • Plan of attack
    01:45
  • Theory
    07:45
  • Implementation
    17:42
  • Debug
    08:58
  • Homework instruction
    00:38
  • Homework solution
    05:10
  • Additional reading
    00:11

  • Plan of attack
    01:27
  • Theory
    06:28
  • Implementation
    19:32
  • Debug
    13:34
  • Homework instruction
    00:38
  • Homework solution
    05:47
  • Additional reading
    00:07

  • Plan of attack
    02:00
  • Preview11:50
  • Implementation 1 - mutation
    09:23
  • Implementation 2 - crossover
    06:14
  • Implementation 3 - genetic algorithm
    19:58
  • Debug
    12:10
  • Homework instruction
    00:21
  • Homework solution
    01:56
  • Comparing the results
    03:38
  • Additional reading
    00:14

  • Plan of attack
    01:42
  • Preview05:58
  • Defining the domain
    13:49
  • Printing the solution
    13:13
  • Fitness function
    10:24
  • Optimization algorithms
    05:59
  • Comparing the results
    02:20

  • Plan of attack
    02:05
  • Preview03:52
  • Domain and printing the solution
    13:23
  • Fitness function
    05:34
  • Optimization algorithms
    07:05
  • Comparing the results
    02:45

  • Plan of attack
    01:43
  • MLROSe library 1
    08:26
  • MLROSe library 2
    08:05
  • Homework instruction
    00:12
  • Homework solution
    07:08

  • Final remarks
    01:36

Instructors

Jones Granatyr
Professor
Jones Granatyr
  • 4.6 Instructor Rating
  • 23,399 Reviews
  • 95,806 Students
  • 59 Courses

Olá! Meu nome é Jones Granatyr e já trabalho em torno de 10 anos com Inteligência Artificial (IA), inclusive fiz o meu mestrado e doutorado nessa área. Atualmente sou professor, pesquisador e fundador do portal IA Expert, um site com conteúdo específico sobre Inteligência Artificial. Desde que iniciei na Udemy criei vários cursos sobre diversos assuntos de IA, como por exemplo: Deep Learning, Machine Learning, Data Science, Redes Neurais Artificiais, Algoritmos Genéticos, Detecção e Reconhecimento Facial, Algoritmos de Busca, Mineração de Textos, Buscas em Textos, Mineração de Regras de Associação, Sistemas Especialistas e Sistemas de Recomendação. Os cursos são abordados em diversas linguagens de programação (Python, R e Java) e com várias ferramentas/tecnologias (tensorflow, keras, pandas, sklearn, opencv, dlib, weka, nltk, por exemplo). Meu principal objetivo é desmistificar a área de IA e ajudar profissionais de TI a entenderem como essa tecnologia pode ser utilizada na prática e que possam visualizar novas oportunidades de negócios.

IA Expert Academy
Professor
IA Expert Academy
  • 4.6 Instructor Rating
  • 21,341 Reviews
  • 62,634 Students
  • 57 Courses

A plataforma IA Expert tem o objetivo de trazer cursos teóricos e práticos de fácil entendimento sobre sobre Inteligência Artificial e Ciência de Dados, para que profissionais de todas as áreas consigam entender e aplicar os benefícios que a IA pode trazer para seus negócios, bem como apresentar todas as oportunidades que essa área pode trazer para profissionais de tecnologia da informação. Também trazemos notícias atualizadas semanais sobre a área em nosso portal.

Ligency Team
Helping Data Scientists Succeed
Ligency Team
  • 4.5 Instructor Rating
  • 469,355 Reviews
  • 1,686,228 Students
  • 109 Courses

Hi there,

We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology.

See you in class,

Sincerely,

The Real People at Ligency

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