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What you will 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 optimizing flight calendars and dormitory room optimization (limited resources)
  • Implement optimization 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 ā€œoptimal worldā€ 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

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Lesson Content
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Ratings and Reviews

4.9
Avg. Rating
40 Ratings
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Review posted on Udemy
Posted 2 months ago
by Satendra Singh .

good

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Posted 3 months ago
by Ayyub Arshed Syed

good

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Review posted on Udemy
Posted 4 months ago
by Harshvardhan .

Clearly not doing this cause my org wanted me to ; )

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Review posted on Udemy
Posted 4 months ago
by Neil Walker

It was definitely a lengthy and informative course. The period can even be extended depending on how much work you can devote to the course.

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Review posted on Udemy
Posted 4 months ago
by Ashtyn Houston

The course was great. I understood how to forecast either beneficial or adverse returns using classification techniques.

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Review posted on Udemy
Posted 4 months ago
by Edwin Morales

Very well done. You get the idea that he genuinely cares about his students and wants them to be successful.

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Review posted on Udemy
Posted 4 months ago
by Sigrid Stroman

Amazing course, nicely planned and provided. Covers a wide range of subjects in artificial intelligence.

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Review posted on Udemy
Posted 4 months ago
by Haylee Dooley

Superb for the intermediate to higher level. Each topic is well described in depth, and the instructor explains in a practical way that makes it easy to understand.

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Review posted on Udemy
Posted 1 year ago
by Varun Kumar

fantastic explanation

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Review posted on Udemy
Posted 1 year ago
by Satish Kumar Thakur

It's informative and good contents.

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