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| CS 24300 - Artificial Intelligence Basics |
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Associated Term:
Fall 2024
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. Required Materials: Technical Requirements: |
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