This course provides an introduction to the principles and practice of computer and network security with a focus on both fundamental principles and practical applications through hands-on approach. Many of the principles are taught through examples. The key topics of this course are a brief introduction to computer networking; applied cryptography; protecting users, data, and services; network security, and common threats and defense strategies. Students will complete a number of practical lab assignments as well as auto-graded quizzes/assignments.

Using computers for system design and decision making under uncertainty. Monte Carlo methods, modeling discrete-event stochastic systems, random number generation, time-advance mechanisms, output analysis, simulation-based optimization.

Using computers for system design and decision making under uncertainty. Monte Carlo methods, modeling discrete-event stochastic systems, random number generation, time-advance mechanisms, output analysis, simulation-based optimization.

Introduces students to the principal activities and state-of-the-art techniques involved in developing high-quality software systems. Topics include: requirements engineering, formal specification methods, design principles & patterns, verification & validation, debugging, and automated software engineering.

Introduces students to the principal activities and state-of-the-art techniques involved in developing high-quality software systems. Topics include: requirements engineering, formal specification methods, design principles & patterns, verification & validation, debugging, and automated software engineering.

Recent years have seen a dramatic rise in the use of algorithms for solving problems involving strategic decision makers. Deployed algorithms now assist in a variety of economic interactions: assigning medical residents to schools, allocating students to courses, allocating security resources in airports, allocating computational resources and dividing rent.

Recent years have seen a dramatic rise in the use of algorithms for solving problems involving strategic decision makers. Deployed algorithms now assist in a variety of economic interactions: assigning medical residents to schools, allocating students to courses, allocating security resources in airports, allocating computational resources and dividing rent.

Mathematical and algorithmic foundations of big data processing. Study of methods for sampling, sketching, and distributed processing of large scale databases, graphs, and data streams for purposes of scalable statistical description, querying, pattern mining, and learning.

Mathematical and algorithmic foundations of big data processing. Study of methods for sampling, sketching, and distributed processing of large scale databases, graphs, and data streams for purposes of scalable statistical description, querying, pattern mining, and learning.

The Commonwealth Honors College thesis or project is intended to provide students with the opportunity to work closely with faculty members to define and carry out in-depth research or creative endeavors. It provides excellent preparation for students who intend to continue their education through graduate study or begin their professional careers. The student works closely with their 499Y Honors Research sponsor to pursue research on a topic or question of special interest to them in preparation for writing a 499T Honors Thesis or completing a 499P Honors Project.