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| CS 24300 - Artificial Intelligence Basics | |||||||||||||||||||||
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Credit Hours: 3.00. This course provides an introduction to foundational areas of artificial intelligence and current techniques for building intelligent systems. As an entry-level course for Artificial Intelligence, the primary goals of this course are: Teach fundamental building blocks of an intelligent system, namely, knowledge representation; learning; model validation, diagnosis, and visualization; reasoning and decision-making; probabilities and uncertainty in AI. Provide students with first-hand experiences in building a working machine learning and an automated reasoning system. Provide an overview of current state-of-the-art technologies in multiple domains of artificial intelligence. Broaden the students' horizon and spark their interests via learning about exciting applications of artificial intelligence in many aspects of human society.
0.000 OR 3.000 Credit hours Syllabus Available Levels: Undergraduate, Graduate, Professional Schedule Types: Distance Learning, Laboratory, Lecture All Sections for this Course Offered By: College of Science Department: Computer Science Course Attributes: Lower Division May be offered at any of the following campuses: Indianapolis and W Lafayette West Lafayette Learning Outcomes: 1. Use data processing and implement learning and reasoning algorithms using Python. 2. Determine how to represent knowledge in an AI system. 3. Build a first-hand machine learning system. Know and be able to build all basic components of the entire machine learning pipeline, including data collection, wrangling, cleaning, model selection, training, cross-validation, and diagnosis. 4. Master the mathematical theory behind linear regressors and classifiers. 5. Build a first-hand automated reasoning system, learn how to formulate real-world problems as constraint programs, solve reasoning problems and make complex decisions using AI. 6. Produce a reasoning system using depth-first search. 7. Demonstrate basic knowledge of the full landscape of AI: game playing, causality, fairness/bias/ethics, uncertainty handling, reinforcement learning. Restrictions: Must be enrolled in one of the following Majors: Artificial Intelligence Artificial Intelligence Prerequisites: Undergraduate level MA 16100 Minimum Grade of C or Undergraduate level MA 16300 Minimum Grade of C or Undergraduate level MA 16500 Minimum Grade of C or Undergraduate level MATH 16500 Minimum Grade of C or Undergraduate level MA 16700 Minimum Grade of C or (Undergraduate level MA 22100 Minimum Grade of C and Undergraduate level MA 22200 Minimum Grade of C or Undergraduate level MA 16021 Minimum Grade of C) or (Undergraduate level MA 22300 Minimum Grade of C and Undergraduate level MA 22400 Minimum Grade of C) or (Undergraduate level MA 16010 Minimum Grade of C and Undergraduate level MA 16020 Minimum Grade of C) and Undergraduate level CS 18000 Minimum Grade of C and Undergraduate level CS 18200 Minimum Grade of C Short Title: Artificial Intelligence Basics Course Configurations:
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