Syllabus and Course Schedule

DateTopicsMaterials and Assignments
Aug 23Introduction Slides
Survey
Aug 28Demystifying AI, The Big PictureSlides
Reading Assignment: Deep Learning, Chapter 1: Introduction (pages 1-26)
The book is online for free, including this chapter. See
Textbooks and Resources menu.
Aug 30Programing And Development ToolsSlides
Reading Assignment: The NumPy array: a structure for efficient
numerical computation
Sep 4Searching as an AI MechanismSlides
Sep: 6Informed Searching: Genetic AlgorithmSlides
Homework Assignment
Sep 11Probability and Statistics for AI &
Machine Learning I		Slides
Reading Assignment
Sep 13No class due to Hurricane Florence
Sep 18Probability and Statistics for AI &
Machine Learning II		Slides
Sep 20Linear Algebra for AI &
Machine Learning I 		Slides

Naive Bayes for document classification: description and homework assignment
Sep 25Linear Algebra for AI &
Machine Learning II 		Slides
Sep 27Linear Models I Slides
Oct 2Linear Models II, Gradient Descent Methods for OptimizationSlides

Logistic Regression and Homework Assignment
Oct 9Multilayer Perceptron I: IntroductionSlides
Oct 11Multilayer Perceptron II: Cost Functions and ApplicationsSlides
Oct 16Multilayer Perceptron III: TrainingSlides

Homework: PCA+ANN
Oct 18Exam ReviewSlides
Oct 23Midterm ExamMidterm Exam
Oct 25Overfitting/UnderfittingSlides
Oct 30Convolutional Neural Networks ISlides
Nov 1Convolutional Neural Networks IIHomework assignment
Nov 6Recurrent Neural Network ISlides
Nov 8Recurrent Neural Network IISlides
Nov 13CNN homework, Regularization, and Recurrent Neural Network III
Nov 15RNNs, LSTM, GRU.Slides
Nov 20Homework for word embedding, project presentationsSlides
Nov 27Generative Adversarial Networks I, Ethics and Fairness in AISlides
Nov 29Generative Adversarial Networks II, Ethics and Fairness in AISlides
Dec 4Reinforcement Learning ISlides
Dec 6Reinforcement Learning II, Final Exam ReviewSlides
Dec 13Final ExamFinal Exam