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Artificial Intelligence

Artificial Intelligence

This course gives a survey of topics in AI along with in-depth foundational concepts such as classical search, probability, machine learning, logic and planning.
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Summary

Learn about the fundamentals of Artificial Intelligence in this introductory graduate-level course. It provides a survey of various topics in the field along with in-depth discussion of foundational concepts such as classical search, probability, machine learning, logic and planning.

Expected Learning

Artificial Intelligence is poised to become one of the most revolutionary technologies of our time. We interact with intelligent systems and services in various forms, including apps on our phones, websites, devices, etc. With that, the demand for AI Engineers is on the rise. Take this course to understand the fundamental concepts and algorithms behind artificial intelligence, and learn to apply them to various real-world problems including game playing, navigation, sign-language recognition, et al.

Syllabus

Search

  • Game Playing
  • Basics of Search
  • Logic and Planning

Constraints and Bayes Nets

  • Constraint Satisfaction
  • Probability
  • Bayes Nets

Basics of Machine Learning

  • Simulated Annealing
  • Machine Learning
  • Pattern Recognition through Time

Required Knowledge

Undergraduate computer algorithm and data structures courses that cover O notation, time and space constraints; working knowledge of college level mathematics such as calculus, probability, and linear algebra. You will also need to be familiar with Python and be comfortable making modifications to large programs.

Please review the following questions, if you answer "no" to any of them you may want to refresh your knowledge or practice the required skills prior to taking the class:

  • Are you comfortable programming in Python, including IPython notebooks? If not, are you comfortable in learning a language within the first week of class?
  • Have you taken several classes that required intensive programming?
  • Have you taken algorithms and data structures courses?
  • Are you prepared to spend at least 9 hours a week on this class?

Pricing:
Free
Level:
Intermediate
Duration:
17 weeks
Educator:
Thad Starner
Organization:
Georgia Institute of Technology
Submitted by:
Coursearena
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