New! Robotics Programming Concentration
Partnership with Miller Fabrication Solutions
The Department of Computer Information Science is partnering with Miller Fabrication Solutions for an upcoming robotics programming concentration in both the Computer Science and the Information Systems degrees. Miller Fabrication Solutions employs robot programmers and will help shape the robotics programming concentration so that CIS graduates will be employable at their company.
courses in the robotics Programming Concentration
The robotics programming concentration is under development and it is contingent on student interest. Therefore, the course content can change. The current courses and descriptions are:
Introduction to Robotics Programming. A lab-based course that uses a hands-on approach to introduce the basic concepts of robotic in conjunction with the programming skills learned in previous courses through programming of autonomous mobile robots. Course information will be tied to lab experiments: students will work in groups to build and test increasingly more complex mobile robotic algorithms,
Artificial Intelligence in Decision Making. Surveys the thinking and some of the pioneering efforts in the area of artificial intelligence (AI), integrated with more traditional approaches to decision-making. Applies AI principles through the use of logic programming languages.
Autonomous Robotics. This course aims to introduce students into the holistic design of autonomous robots to include sensors and intelligence. The course contains modules state estimation robot vision, Simultaneous Localization and Mapping and object detection, and path planning. A semester-long student project helps to equip student with robot development skills.
Machine Learning. This course introduces various machine learning concepts and algorithms. Students will learn about the basics of machine learning as well as how machine learning is used during interactions in their everyday lives. Students will also be exposed to machine learning through a programming framework of GUI application (for example, Weka). Although machine learning is inherently mathematical, this course focuses on understanding algorithms at a high level and being able to apply and compare them rather that the low-level mathematics or implementations.
Natural Language Processing. The natural language processing field is the intersection between human language and computer science. This course provides an introduction to the field of natural language processing. Students will learn how computers acquire, understand and generate human language. How can computers translate text between different languages? How can google find the web page that you ask for? How do email systems filter junk mail?. How can voice recognition software and text to speech software work? This course will expose students to those techniques using a range of statistical methods and machine learning methods. Students will also practice writing NLP software.