54 FALL 2024 925.424.1000 | [email protected] FALL 2024 - COURSE LISTINGS Please refer to the online schedule on CLASS-Web to access course section details and the course record numbers (CRNs) for registration. CS 7 INTRO TO COMPUTER PROGRAMMING 3.0 Units An introductory course in computer programming concepts and fundamental coding skills using object-oriented languages like Python. Material includes problem-solving techniques, design of algorithms, and common programming constructs such as variables, expressions, input/output, decision-making, loops and arrays. CS 17 DISCRETE MATH STRUCTURES 4.0 Units Designed for majors in mathematics and computer science, this course provides an introduction to discrete Science and their applications. Course content includes: Propositional and predicate logic; rules of inference; quantifiers; elements of integer number theory; set theory; methods of proof; induction; combinatorics and discrete probability; functions and relations; recursive definitions and recurrence relations; elements of graph theory and trees. Applications include: analysis of algorithms, Boolean algebras and digital logic circuits. Students who have completed, or are enrolled in, MATH 10 may not receive credit. Prerequisite: MATH 1 and CS 1 with a minimum grade of C (May be taken concurrently) CS 20 ADV PROG W/DATA STRUCTURES/C++ 4.0 Units Design and implementation of complex programs in C++ using a variety of fundamental data structures and algorithms. Includes the design and implementation recursive functions, of abstract data types, linked lists, stacks, queues, binary trees, hash tables, search and sorting algorithms, graphs, heaps, and algorithm analysis. Recommended Course Preparation: CS 2 with a minimum grade of C CS 21 ASSEMBLY LANGUAGE PROGRAMMING 4.0 Units Basics of machine architecture, cpu architecture and design, machine language, assembly language, operating system and higher level language interface. Data representation, instruction representation and execution, addressing techniques and use of macros. Space and time efficiency issues. Input/output including video modes. Procedures including parameter passing and linkage to higher level languages. Prerequisite: CS 1 with a minimum grade of C CS 31 JAVA PROGRAMMING 4.0 Units Applications programming using Java for students already familiar with the concepts of programming. Topics will include in Applets GUI programming and design using Swing, presenting data files over the web, elementary data structures (queues, linked list, stacks) and vectors, searching (linear, binary), sorting algorithms, Database programming using JDBC (Java Data Base Connectivity), Remote Method Invocation (RMI), and Java Beans. The student shall also be exposed to and experience developing Java applications and applets in the Linux/Unix environment(s) Recommended Course Preparation: CS 1 and CS 7 with a minimum grade of C CS 41 RED HAT LINUX ADMIN. I 3.0 Units This course provides hands-on training covering basic installation, management, configuration, documentation and hardware topics for the Linux/UNIX operating system on workstations in a network environment. The course includes comprehensive coverage of topics related to Linux distributions, installation, administration, X-Windows, and networking. Students who have completed or are enrolled in CNT 7401 may not receive credit. Recommended Course Preparation: CIS 50 with a minimum grade of C dynamic address allocation in IPv6 networks by using SLAAC and DHCPv6; how FHRPs provide default gateway services in a redundant network; how vulnerabilities compromise LAN security; how Wireless LANs enable network connectivity; how routers use information in packets to make forwarding decisions; and troubleshooting static and default route configurations. The hands-on labs include Basic Configuration of devices by using security best practices; Implementing VLANs and trunking in a switched network; Troubleshooting inter-VLAN routing on Layer 3 devices; Troubleshooting EtherChannel on switched links; Implementing DHCPv4 to operate across multiple LANs; Configuring switch security to mitigate LAN attacks; Implementing a WLAN using a wireless router and WLC; configuring and troubleshooting IPv4 and IPv6 floating static routes. Recommended Course Preparation: CNT 8001 with a minimum grade of C COMPUTER SCIENCE CS 1 COMPUTING FUNDAMENTALS I 4.0 Units Introduction to programming and problem-solving using C++. Problem solving techniques and algorithms; program design, development, style, testing and debugging. C++ syntax covered includes: variables; data types; operators and expressions; control structures; library and user- defined functions; basic file input/output; binary file input/output; arrays; vectors; abstract data types including user-defined data structures and enumerated data types. Recommended Course Preparation: MATH 107 and CS 7 with a minimum grade of C CS 2 COMPUTING FUNDAMENTALS II 4.0 Units Application of software engineering techniques to the design and development of large programs. Object-oriented programming methods and problem-solving strategies applied to intermediate-level problems using C++. Includes pointers and dynamic allocation; classes; encapsulation; inheritance and polymorphism; object and function overloading; recursive algorithms; data abstraction and structures. Prerequisite: CS 1 with a minimum grade of C CS 3 RED HAT LINUX ADMIN. II 3.0 Units This course focuses on the key tasks needed to become a full time Linux Administrator and to validate those skills via the Red Hat Certified System Administrator exam. This course goes deeper into Enterprise Linux administration including filesystems and partitioning, logical volumes, SELinux, firewalling, BASH script development and troubleshooting. Students who have completed or are enrolled in CNT 7402 may not receive credit. Recommended Course Preparation: CS 41 with a minimum grade of C CS 4 INTRO- ARTIFICIAL INTELLIGENCE 3.0 Units An introduction to artificial intelligence (AI) and modern AI programming libraries. Basic discrete mathematics and statistics. Problem solving using uninformed, informed, local, and adversarial search algorithms. Knowledge representation, inference, and reasoning using propositional and first-order logic. Quantifying and reasoning about uncertainty with Bayesian networks and Markov decision processes. Ethical considerations of artificial intelligence. Prerequisite: CS 1 with a minimum grade of C Recommended Course Preparation: CS 7 and MATH 40 with a minimum grade of C
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