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You will learn the strengths and weaknesses of various computational and artificial intelligence (AI) techniques using supplied software.
The course introduces the following topics:
- Search spaces and their importance for assessing problem complexity
- Evolutionary computation, the fundamental engine behind many AI techniques
- Genetic programming with many examples
- Neural networks and the iris problem
- Swarm intelligence, the power of collective, decentralized systems
- Support vector machines demonstration using a popular tool for simple classification
- Fuzzy logic, including a solution of the traveling salesman problem
You will learn to solve AI problems using software on a provided bootable USB Stick and learn techniques for representing and structuring real-world problems using AI. By the end of the course, you will understand common algorithms and techniques used to solve real-world optimization problems, and also gain experience applying them to practical problems.
At the conclusion of the course, you should be able to
- Determine if a particular task is suitable for a computational intelligence technique
- Apply the appropriate methods to the problem of interest.
Skills Needed: Experience with a computer programming language and basic algebra skills.
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