Associate of Applied Science Degree in Artificial Intelligence

The Associate of Applied Science Degree in Artificial Intelligence implements Intel’s AI for Workforce program. The content includes introductions to artificial intelligence, machine learning, natural language processing, computer vision, and artificial intelligence for business solutions and other applications. The curriculum also includes coursework in computer programming, mathematics, and statistics. Intel offers additional instructional content that allows students to develop skills in data collection, AI model training, coding, and exploring the societal impact of AI technology.

The program is designed as a two-year work force program that prepares students for entry-level positions in artificial intelligence and related fields. Students who wish to pursue a four-year degree have post-graduation opportunities at the University of Cincinnati and other colleges or universities. Graduates of the program will be prepared to enter computer science, information technology, mathematics, statistics, and business programs.

CS1010: Introduction to Artificial Intelligence

This is a first course in basic concepts and applications of artificial intelligence (AI) including ethical issues and the roles of AI in everyday life. The course will focus on issues surrounding AI including application workflows, skill sets, ethics, bias, culture, regulations, and professional expectations. Discussions will include AI applications in machine learning, natural language processing, and computer vision. Students will use visual programming environments to implement and evaluate elementary AI applications.
This course is not accepted for the BSCS, BSCMPE, BSEE, BSEET degree programs in CEAS.

CS1015C Fundamentals of Applied Programming

Fundamentals of Applied Programming introduces essential programming for the purposes of accessing data, performing analyses, and developing applications. Concepts covered include data types, expressions, variables, assignments, conditional and iterative structures, functions/methods, arrays/lists, file input/output, exceptions, user-defined classes, and the use of libraries.

CS1050C Applied Mathematics for AI

A survey of selected topics in statistics, linear algebra, probability, and calculus that are relevant to the understanding and implementation of AI applications. The course focuses on computer programming implementations of these topics in AI applications.

CS1060C Machine Learning

Introduction to machine learning concepts and applications, including supervised, unsupervised and reinforcement learning models. The course focuses on the use of industry standard platforms and libraries to implement and evaluate machine learning applications.

CS2000C Computer Vision

Fundamental concepts in Computer Vision (CV) and image processing, including an introduction to the mathematics of computer vision and the use of industry standard computer vision platforms and libraries. The course focuses on the knowledge and skills necessary to create a computer vision application using standard industry computer vision libraries.

CS2040C Natural Language Processing

Fundamental concepts in Natural Language Processing (NLP). The course focuses on knowledge and skills necessary to create a natural language processing application using available NLP libraries.

CS2085C AI Capstone

The course will provide an opportunity for students to reflect on learning completed throughout the AI program and engage in high-level inquiry focusing on an area of specialization within AI which can include machine learning, computer vision and/or natural language processing. Capstone projects will be inquiry and practice-centered and will draw upon areas of focus from the program.

• Faculty & Staff
  

Associate Professor Trevor Presgrave
AI Program Director
Email: presgrta@ucmail.uc.edu