Lecture, discussion. Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Graphs, trees, and search. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem. Problem sets, 2 midterm exams, timed final.

Lecture, discussion. Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Graphs, trees, and search. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem. Problem sets, 2 midterm exams, timed final.

This is a class devoted to the study of securing distributed systems, with blockchain-based cryptocurrencies serving as our real platform of interest. We'll start with the fundamentals of Lamport's, Fischer's, and Douceur's results that fence-in all consensus system, and discuss Byzantine fault tolerance. We'll also look at the efficiency of the network architectures for peer-to-peer;distributed system communication and attacks on their security, such as denial of service attacks. And we'll review relevant applied cryptography such as elliptic curves.

Game Programming introduces students to concepts of computer game development, including 2D and 3D modeling, character design, animation, game art, basic game AI, audio and video effects. The course will help students build the programming skills needed to turn ideas into games. Both runtime systems and the asset pipelines will be covered. Students will work on various game programming exercises with modern game engines and graphics APIs. This course counts as a CS Elective toward the CS major (BA or BS).

Game Programming introduces students to concepts of computer game development, including 2D and 3D modeling, character design, animation, game art, basic game AI, audio and video effects. The course will help students build the programming skills needed to turn ideas into games. Both runtime systems and the asset pipelines will be covered. Students will work on various game programming exercises with modern game engines and graphics APIs. This course counts as a CS Elective toward the CS major (BA or BS).

Much recent work in computer science in a variety of areas, from game theory to machine learning and sensor networks, exploits sophisticated methods of optimization. This course is intended to give students an in-depth background in both the foundations as well as some recent trends in the theory and practice of optimization for computer science. There is currently no course in the department that covers these topics, and yet it is critical to a large number of research projects done within the department.

Data science uses various concepts, practices, algorithms, and systems to extract knowledge and insights from data. It encompasses techniques from machine learning, statistics, databases, visualization, and several other fields. When properly integrated, these techniques can help human analysts make sense of vast stores of digital information.

This course will introduce students to the field of mobile sensing and ubiquitous computing (Ubicomp) - an emerging CS research area that aims to design and develop disruptive technologies with hardware and software systems for real-world messy, noisy and mobile scenarios. The students will learn how to build mobile sensing systems, how to implement it with ubiquitous computing tools, how to make sense of the sensor data and model the target variables.

This course will introduce students to the field of mobile sensing and ubiquitous computing (Ubicomp) - an emerging CS research area that aims to design and develop disruptive technologies with hardware and software systems for real-world messy, noisy and mobile scenarios. The students will learn how to build mobile sensing systems, how to implement it with ubiquitous computing tools, how to make sense of the sensor data and model the target variables.

Computing has become data-driven, and databases are now at the heart of commercial applications. The purpose of this course is to provide a comprehensive introduction to the use of data management systems within the context of various applications. Some of the covered topics include application-driven database design, schema refinement, implementation of basic transactions, data on the web, and data visualization.