rama25 / cs540

CS 540 Intro to AI UW Madison

CS540 AI UW Madison

Learn fundamental principles of different areas of artificial intelligence, including knowledge-based search techniques; automatic deduction, knowledge representation using predicate logic, machine learning, probabilistic reasoning. Develop applications in tasks such as problem solving, data mining, game playing, natural language understanding, and robotics.

Understand and be able to apply the foundational tools in Machine Learning and Artificial Intelligence: Linear algebra, Probability, Logic, and elements of Statistics.

Understand core techniques in Natural Language Processing, including bag-of-words, tf-idf, n-Gram Models, and Smoothing.

Understand the basics of Machine Learning. Identify and summarize important features in supervised learning and unsupervised learning.

Distinguish between regression and classification, and understand basic algorithms: Linear Regression, k-Nearest Neighbors, and Naive Bayes.

Understand the basics of Neural Networks: Network Architecture, Training, Backpropagation, Stochastic Gradient Descent.

Learn aspects of Deep Learning, including network architectures, convolution, training techniques.

Understand the fundamentals of Game Theory.

Understand how to formulate and solve several types of Search problems.

Understand basic elements of Reinforcement Learning.

Consider how Artificial Intelligence and Machine Learning problems are applied in Real - World settings and the Ethics of Artificial Intelligence.