Artificial Intelligence: Optimization Algorithms in Python
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 optimisation 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
3 lectures • 11minIntroduction
- Preview04:37
- Preview05:43
- 00:16Source code and slides
11 lectures • 1hr 40minRepresentation of AI problems - group travel
3 lectures • 23minRandom search
7 lectures • 42minHill climb
7 lectures • 48minSimulated annealing
10 lectures • 1hr 8minGenetic algorithm
7 lectures • 53minLimited resources - bedrooms problem
6 lectures • 35minMaximizing profit - transport of products
5 lectures • 26minLibrary for optimization algorithms
1 lecture • 2minFinal remarks
Instructors
![Jones Granatyr](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.6 Instructor Rating
- 19,996 Reviews
- 56,365 Students
- 52 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.
- 4.5 Instructor Rating
- 452,722 Reviews
- 1,498,948 Students
- 118 Courses
My name is Kirill Eremenko and I am super-psyched that you are reading this!
Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes.
From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events.
To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!
- 4.5 Instructor Rating
- 239,879 Reviews
- 1,073,575 Students
- 80 Courses
Hadelin is the co-founder and CEO at BlueLife AI, which leverages the power of cutting edge Artificial Intelligence to empower businesses to make massive profits by innovating, automating processes and maximizing efficiency. Hadelin is also an online entrepreneur who has created 70+ top-rated educational e-courses to the world on topics such as Machine Learning, Deep Learning, Artificial Intelligence and Blockchain, which have reached 1M+ students in 210 countries.
- 4.5 Instructor Rating
- 417,124 Reviews
- 1,414,257 Students
- 103 Courses
Hi there,
We are the SuperDataScience Social team. You will be hearing from us when new SDS 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 SuperDataScience