Foundations of A.I.: Search Algorithms
About this course
This course is designed for all enthusiasts who are interested for a career in Artificial Intelligence. The main objective of this course is to give a solid foundation of the good old Artificial Intelligence concepts which includes the definition of Artificial Intelligence, different schools of Thought, a tinge of Sir Alan Turing's thoughts about Computational Thinking. As we progress into the course, we will try to understand the significance of graphs and how any problem can be represented as a Graph. At the heart of this course is Search Algorithms, we will have a look at methods that allow computers to search for solution in a huge solution space. In that pursuit, we will work with Uninformed Search and Informed Search Algorithms. Informed Search algorithms have their foot print in Robotics, Navigation systems, designing games and many more. Course is incomplete if we leave with informed search, to counter the problems of search algorithms, we will look into local search which will eventually land in Optimization. In local search, we will work with Hill climbing algorithms along with their disadvantages. To sum up, this course gives answers to questions raised by students who want to explore the fundamentals difference between human intelligence and machine intelligence.
63/100
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- What the provider tells you
- 39/45
- Who stands behind it
- 8/35
- How complete the listing is
- 16/20
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What you'll learn
- understanding of artificial intelligence concepts
- familiarity with graph representation of problems
- knowledge of uninformed and informed search algorithms
- ability to apply local search techniques like hill climbing
Course objectives
- to provide a solid foundation in artificial intelligence
- to explain the significance of search algorithms
- to compare and contrast human intelligence with machine intelligence
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