The University at Buffalo offers several undergraduate courses related to networking, computing and artificial intelligence.
Not all courses are offered every semester, so be sure to view the Class Schedules to see when courses will be available.
Explore undergraduate courses in Computing and Network Management. These 3-credit courses are all offered entirely online and be taken for credit toward your undergraduate degree.
This course will take you beyond the surface of computer basics and help you to understand the foundation behind the technology. Topics will include the importance of the interdependence between hardware and software; networking - including the set up of a home or small office network; mobile devices and wireless connectivity; problem-solving strategies that apply to computer program development as well as problems in the business world; and current computer-related careers. Additionally, applications like Word, Excel, PowerPoint, Access and basic Web design will be used to solve practical problems and create documents that relate to real-world situations.
Intended to introduce the fundamentals of systems administration using the Linux Operating System. Emphasis is placed on command line and GUI tools to enable the daily use of Linux for productivity. On completion of this course, a student should be comfortable not only using the Linux Operating System for daily administrative and desktop tasks but, also feel comfortable establishing Linux Server components for enterprise class functionality.
To present an in-depth overview of the Internet, its components, and its place in business. Analyzing the emerging technologies used in today's networks, with emphasis on Cloud computing, VMware, NAS, LANDesk, web sense, netapp, citrix, WebEx, VoIP, amazon web services, Microsoft Azure services and server virtualization (VMWARE). These topics are subject to change each semester but the emphasis will be on cloud computing's latest technology and its use in Business. This course is the same as MFC 305 and course repeat rules will apply. Students should consult with their major department regarding any restrictions on their degree requirements.
The principals of security will be offered as a vendor-neutral IT security course with topics recognized worldwide as best practice necessities. The material presented will provide a comprehensive study of network and host security. This course will cover basic security principles, establishing security baselines, and the most recent attack and defense techniques and technologies. In addition, techniques used to harden a network to resist attacks, protect basic and advanced communications, and use cryptography and Public Key Infrastructure (PKI) to thwart attackers. The establishment of security policies and procedures and managing security efforts so that students are prepared for the ongoing challenge of securing data will also be introduced.
Surveys the discipline of telecommunications in today's deregulated environment for current or prospective managers of telephone and data communications systems. Topics include fundamental voice and data concepts, network design, customer premise equipment and central office equipment, modes of transmission, marketing and regulations issues, management of systems, and future directions. No prior technical background is required.
Analyzes the methodologies and components used in communicating voice and data information by means of digital signals. Topics include fundamental concepts; characters and codes; communication lines, fiber optics, and satellite communications; terminals, modems, and interfaces; protocols; local area and packet networks; and network design, devices, and management.
Artificial Intelligence appears in many practical situations: from problems such as returning relevant text to a vague question to robotic cars that need to safely navigate chaotic traffic. As a result, AI is frequently in the news for both important ethical questions and practical breakthroughs. This course is an introduction to AI for junior and senior level students. The goal is to put these topics into a common perspective and to give you practical hands-on skill in solving AI problems through programming assignments.
Involves teaching computer programs to improve their performance through guided training and unguided experience. Takes both symbolic and numerical approaches. Topics include concept learning, decision trees, neural nets, latent variable models, probabilistic inference, time series models, Bayesian learning, sampling methods, computational learning theory, support vector machines, and reinforcement learning.