Reasoning Under Uncertainty

Development of mathematical reasoning skills for problems that involve uncertainty. Counting and probability -- basic counting problems, probability definitions, mean, variance, binomial distribution, discrete random variables, continuous random variables, Markov and Chebyshev bounds, Laws of large number, and central limit theorem. Probabilistic reasoning -- conditional probability and odds, Bayes' Law, Markov Chains, Bayesian Network, Markov Decision Processes.

Computer Systems Principles

Large-scale software systems like Google - deployed over a world-wide network of hundreds of thousands of computers - have become a part of our lives. These are systems success stories - they are reliable, available ("up" nearly all the time), handle an unbelievable amount of load from users around the world, yet provide virtually instantaneous results.

Intro to Computer Graphics

This course introduces the fundamental concepts of two-dimensional (2D) and three-dimensional (3D) computer graphics. It covers the basic methods needed to model, render, and animate 3D objects. Topics include raster displays, line drawing, affine and perspective transformations, windows and viewpoints, clipping, visibility, illumination models, reflectance models, radiometry, curves and surfaces, shading, texture mapping, ray tracing, graphic toolkits, animation, and 3D printing.

Formal Language Theory

Introduction to formal language theory. Topics include finite state languages, context-free languages, the relationship between language classes and formal machine models, the Turing Machine model of computation, theories of computability, resource-bounded models, and NP-completeness. It is recommended that students have a B- or better in COMPSCI 311 in order to attempt COMPSCI 501.

Introduction To Computation

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.

Distributed&Operating Systems

An in-depth examination of principles of distributed operating systems. Topics include processes and threads, concurrent programming, distributed interprocess communication, distributed process scheduling, shared virtual memory, distributed file systems. MACH. Familiarity with an undergraduate course on operating systems (CMPSCI 377 or equivalent) is helpful.
Subscribe to