This course introduces students to the field of artificial intelligence (AI) through investigation of some of the basic structures in use. As AI is becoming ever more prevalent in a variety of industries, such as the automotive, aerospace, technology, industrial design and gaming industries, a diverse selection of AI strategies will be considered. Topics to be covered include automatons, decision structures, Bayesian networks, machine learning, and neural networks. Students will build AI agents to solve simple problems . Prerequisites: CISC 3323 and MATH 1430. Lab fee.
3
Introduction to database systems. Relational database topics include data modeling, query languages, database design, and query optimization. Alternative data management approaches will be converted including semi-structured data, XML, and text retrieval. Application topics will include web data management, integration of data sources, security, and data mining. Prerequisites: CISC 3322. Lab fee.
3
This course will examine the theories and applications to analyze the big data. It will introduce the big data cloud computing environment and various applications such as Hadoop, Spark and Hive that can be integrated with various database systems and machine learning algorithms. Lab fee. Prerequisite: CISC 3323. Lab fee.
3
This course will examine various data types and methods to analyze and visualize the data. It will cover the data pipeline: data collection, cleaning, exploration, modeling, visualization and applications. Lab fee. Prerequisite: CISC 3323. Lab fee.
3
In this course, students work both independently, and in groups, to develop, either from the scratch or template, meaningful graphical games using the JAVA language. Students study various graphical game engines & techniques, i.e. real-time 2D/3D graphics, lighting, terrain and texture mapping, visibility and occlusion, collision detection and avoidance, character animation, and Artificial Intelligence characters. We will explore two-dimensional and three-dimensional renderings of mathematical and scientific data (such as fractals), as well as photo-realistic objects using C++. Important notice: At least fifteen (15) contact hours, as well as a minimum of thirty (30) hours of student homework is required for each credit hour. Mode of delivery will consist of lectures and lab work. Prerequisite: CISC 3321 or equivalent. Lab fee.
3