AP/ITEC 4310 3.00
Applied Artificial Intelligence
A brief survey to the theory and development of artificial intelligence (AI) leading to current models of application and deployment. AI topics include: symbolic AI, predicate logic, artificial neural nets (including back propagation, training, and testing), big data, deep learning, computational intelligence (e.g. nature-based metaphors, fuzzy logic), clustering, classifiers, feature selection, Bayesian analysis, natural language processing, computer vision, autonomous vehicles, and other current applications. Deployment topics include: service-oriented computing, platform computing, cloud-based computing, etc.
Full hands-on training with one example of a commercial AI service platform. Lectures and tutorial-style homework assignments will cover practical topics such as setting up an account, using cloud services, developing a chatbot, performing largescale analytics, etc.
A large project assignment will provide course participants with an opportunity to build an AI-based application. Students will work individually or in teams to develop and present an AI-based application of their own choosing. Instructor guidance will be provided, and in-class participation grades will be based on weekly progress.