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Home Academics Programs and Majors Computer Information Science

Computer Information Science

Overview Degrees/Certificates Courses Faculty

Computer Information Science - Applications (CISA) Courses

CISA 299 Experimental Offering in Computer Information Science - Applications

  • Units:0.5 - 4
  • Prerequisite:None.
  • Catalog Date:August 1, 2024

This is the experimental courses description.

CISA 499 Experimental Offering in Computer Information Science - Applications

  • Units:0.5 - 4
  • Prerequisite:None.
  • Transferable:CSU
  • Catalog Date:August 1, 2024

This is the experimental courses description.

Computer Information Science - Core (CISC) Courses

CISC 310 Introduction to Computer Information Science

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:None.
  • Transferable:CSU; UC
  • General Education:AA/AS Area II(b); AA/AS Area III(b)
  • C-ID:C-ID BUS 140; C-ID ITIS 120
  • Catalog Date:August 1, 2024

This course is an examination of information systems and their role in business. The focus is on information systems, database management systems, networking, e-commerce, ethics and security, computer systems hardware and software components. Students will develop experience applying these concepts and methods through hands-on projects creating computer-based solutions to business problems.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • SLO1: DESCRIBE EXISTING AND EMERGING TECHNOLOGIES AND THEIR IMPACT ON ORGANIZATIONS AND SOCIETY.
  • explain how a computer system works.
  • distinguish the various hardware and software components of a computer system.
  • differentiate between the most commonly used computer operating systems.
  • differentiate between system software and application software.
  • assess the differences between each of the categories of system and application software.
  • evaluate the social issues pertaining to computer technology including ethics, copyright, privacy and security.
  • SLO2: ARTICULATE THE DEVELOPMENT AND USE OF INFORMATION SYSTEMS IN BUSINESS.
  • differentiate between various computer network types and scopes.
  • propose methods for securing business information systems and the secure utilization of Internet resources.
  • discuss and relate the phases of the System Development Life Cycle.
  • recommend methods for accessing business information systems.
  • SLO3: SOLVE COMMON BUSINESS PROBLEMS USING APPROPRIATE INFORMATION TECHNOLOGY APPLICATIONS AND SYSTEMS.
  • construct solutions to common business problems using electronic spreadsheets in Microsoft Excel.
  • manipulate databases using database software in Microsoft Access.
  • build software solutions to business problems using internet technologies.

CISC 315 Introduction to Computer Game Design

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:None.
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course introduces students to the fundamentals of game design with an emphasis in applying those fundamentals to the creation of computer games. Students will explore the various genres of computer games, including hardware and mobile games. No programming skills are required. Students will explore the relationship between player experience and game mechanics.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • articulate the strengths and weaknesses of various published games.
  • articulate the critical game mechanics utilized in various computer and non computer games.
  • hypothesize how specific game mechanics may potentially influence the designed player experience of a specific game.
  • utilize feedback from focus groups to refine the student's game design.

CISC 326 Linux Systems

  • Units:3
  • Hours:36 hours LEC; 54 hours LAB
  • Prerequisite:None.
  • Transferable:CSU
  • Catalog Date:August 1, 2024

This course introduces the Linux operating system for microcomputers. Concepts include kernels, file structures, daemons, and shells. The course will also include procedures for installing software, creation of user accounts, shell commands, scripts, file security, Perl and C scripting, Common Gateway Interface, system installs, administration, security, and graphical user shells such as X-Windows.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • demonstrate the use of basic Linux commands, text editors, and simple system tools.
  • create simple to intermediate scripts to automate tasks, and compile simple C programs in the Linux environment.
  • demonstrate an understanding of basic operating system internals, such as kernels, disk and memory management, threads, and processes.
  • install, configure, and administer an operating system and common systems software such as a web server or a relational database system.
  • determine network requirements and perform network administration tasks such as configuration of network interfaces and firewalls, create users and groups, and configure security settings.

CISC 495 Independent Studies in Computer Information Science - Core

  • Units:1 - 3
  • Hours:54 - 162 hours LAB
  • Prerequisite:None.
  • Transferable:CSU
  • Catalog Date:August 1, 2024

CISC 498 Work Experience in Computer Information Science - Core

  • Units:0.5 - 4
  • Hours:27 - 216 hours LAB
  • Prerequisite:None.
  • Enrollment Limitation:Student must be in a paid or non-paid internship, volunteer opportunity, or job related to career interests.
  • Transferable:CSU
  • General Education:AA/AS Area III(b)
  • Catalog Date:August 1, 2024

This course provides students with opportunities to develop marketable skills in preparation for employment or advancement within the field of Computer Information Science. Course content will include understanding the application of education to the workforce; completing required forms which document the student's progress and hours spent at the work site; and developing workplace skills and competencies. During the semester, the student is required to attend orientation. Students must complete 27 hours of related paid or unpaid work experience for .5 unit. An additional 27 hours of related work experience is required for each additional .5 unit. The course may be taken for a maximum of 16 units. Students should have access to a computer, the Internet, and some computer media such as a USB drive to store data files. Online students must have an email account. Only one Work Experience course may be taken per semester.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • apply industry knowledge and theoretical concepts in a field of study or career as written in the minimum 3 learning objectives created by the student and employer or work site supervisor at the start of the course.
  • manage personal career plans and decision making using industry & workforce information and online resources.
  • behave professionally and ethically, exhibit adaptability, initiative, self-awareness and self-management as needed.
  • exhibit effective communication, collaboration, and leadership skills at work with consideration to workplace dynamics and social and diversity awareness.
  • demonstrate critical and creative thinking skills as they apply to the workplace.

CISC 499 Experimental Offering in Computer Information Science - Core

  • Units:0.5 - 4
  • Prerequisite:None.
  • Catalog Date:August 1, 2024

This is a course designed to give students an opportunity to study topics in Computer Information Science which are not included in the current course offerings. This course may be repeated for credit providing there is no duplication of topics.

Computer Information Science - Data Science (CISD) Courses

CISD 299 Experimental Offering in Computer Information Science - Data Science

  • Units:0.5 - 4
  • Prerequisite:None.
  • Catalog Date:August 1, 2024

This is the experimental courses description.

CISD 300 Introduction to Artificial Intelligence and Data Science

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:Students must have basic familiarity with computers (e.g. working with files, internet searches). Additionally, students should have some knowledge of types of emerging technologies and their impact on organizations and society. No programming background is needed.
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course introduces students to the basics of artificial intelligence (AI) and data science, explore use cases and applications of AI, understand AI concepts and terms like computer vision, natural language processing, machine learning, deep learning, and neural networks. Students will be exposed to various issues and concerns surrounding AI such as ethics and bias. This course does not require any programming.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • explain what AI is and give examples of how AI is being used in the world. Have a basic understanding of what is inside AI and identify AI industry-relevant applications such as predictive maintenance, recommendation system, viral post prediction, quality assurance system…etc.
  • install Jupyter notebook, create notebook, name cells, run cells, create menus, add rich content, export notebooks, use notebook extensions.
  • explain what Machine Learning is, including the definition of deep learning and neural networks. Differentiate among learning and unsupervised learning and reinforcement learning.
  • demonstrate different methods used in creating data visualization using Tableau Public to harness the power of visualization, and how to communicate the results derived from the analysis of the data set.
  • explain what computer vision is, why it is important, how it differs from image processing, what are the basic techniques in computer vision, and list typical problems or tasks pursued in computer vision.
  • identify the meaning of Natural Language Processing, what is NLP used for, how it works, why it is difficult, what are the techniques used in NLP, and current application and technology.
  • explain what AI ethics means and how to apply the AI Ethics principles like Human Rights, Bias, Inclusion, Privacy, Explainable AI, and Level of Autonomy.

CISD 307 Introduction to Machine Learning

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:CISD 300 and CISP 407 with grades of "C" or better
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course introduces students to the basics of machine learning (ML). Topics include understanding the mathematics behind artificial intelligence (AI), and realize the difference between Machine Learning and Deep Learning. Students will be taught different methods to overcome variance and bias.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • distinguish between Machine Learning (ML) and Deep Learning (DL).
  • summarize and implement the mathematics behind the workings of AI using Python.
  • implement different classification and regression ML models using Python.
  • describe the mathematics behind the workings of a recommendation system.
  • examine the working of different reinforcement learning models with the help of applications.
  • students will be able to name and utilize an Artificial Neural Network (ANN) to solve a problem.
  • outline different methods to overcome variance and bias in DL models.
  • implement supervised DL models on the given datasets.
  • structure the DL project according to the AI project cycle.
  • attribute the efficiency of ML and DL models to the various emerging technologies.

CISD 330 Data Analytics with Tableau

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:None.
  • Transferable:UC
  • Catalog Date:August 1, 2024

This course introduces students to the basics of Data Analytics using Tableau which is an end-to-end data analytics platform that allows students to prep, analyze, collaborate, and share big data insights. Tableau builds transparent AI into its platform so students can easily understand how predictions and perceptions emerge and how they are helping to make smarter decisions right in the flow of data analysis.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • understand how to establish connection with data and perform various data preparation steps for visualizing it.
  • discover new ways of analyzing data, through various features built within Tableau.
  • understand metadata filters, parameters, and sets.
  • master special field types and Tableau-generated fields and the process of creating and using parameters.
  • learn how to build charts, interactive dashboards, story interfaces, and how to share your work.

CISD 410 Natural Language Processing

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:CISD 307 with a grade of "C" or better
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course introduces students to the basics of Natural Language Processing (NLP) and how to give the ability of a computer program to understand human language as it is spoken and written, referred to as natural language. It is a component of artificial intelligence (AI).

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • students will be able to understand the basics of Natural Language Processing (NLP), types of NLP sets, and the process of data acquisition.
  • students will be able to apply the steps involved in data curation process and understand data curation tools.
  • students will understand the importance of data visualization in NLP and how to apply the data visualization techniques.
  • students will be able to explore the working of popular text vectorisation methods and compare various vectorization techniques.
  • students will be able to explore and apply the methods of document similarity and vector visualization using various distance measurement techniques.
  • students will be able to describe and apply NLP classifiers to train machine learning models.
  • students will be able to describe and apply NLP classifiers to train machine learning models.
  • students will be able to define Chatbots working, types and applications.

CISD 412 Computer Vision

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:CISD 307 with a grade of "C" or better
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course introduces students to the basics of Computer Vision (CV) which is a subset of Artificial Intelligence that train computers to automatically process, extract and manipulate visual data from images and videos.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • understand the basics of Computer Vision (CV), types, and the theory behind it.
  • understand Data Acquisition for Computer Vision.
  • understand Data Exploration.
  • understand the basics of OpenCV, applications, functions, and implementation.
  • learn about Computer Vision application, facial recognition and object detection.

CISD 499 Experimental Offering in Computer Information Science - Data Science

  • Units:0.5 - 4
  • Prerequisite:None.
  • Catalog Date:August 1, 2024

This is the experimental courses description.

Computer Information Science - Networking (CISN) Courses

CISN 304 Networking Technologies

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:None.
  • Advisory:CISC 310 with a grade of "C" or better
  • Transferable:CSU
  • C-ID:C-ID ITIS 150
  • Catalog Date:August 1, 2024

This course provides a comprehensive survey of local and wide area networks, technologies, protocols, and connectivity. Topics covered include network topologies, the Open Systems Interconnection seven-layer model for communication, communication protocols and standards, access methods, and data translation and transmission equipment and media. This course is intended to prepare students for programming and system administration activities as well as the CompTIA Network+ certification exam.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • describe and differentiate the devices and services used to support communications in data networks and the Internet.
  • describe the role of protocol layers in data networks.
  • evaluate the importance of addressing and naming schemes at various layers of data networks in IPv4 and IPv6 environments.
  • design, calculate, and apply subnet masks and addresses to fulfill given requirements in IPv4 and IPv6 networks.
  • configure a simple Ethernet network using routers and switches.
  • experiment with common network utilities to verify small network operations and analyze data traffic.

Computer Information Science - Programming (CISP) Courses

CISP 300 Algorithm Design/Problem Solving

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:None.
  • Advisory:CISC 310
  • Transferable:CSU; UC
  • General Education:AA/AS Area II(b)
  • Catalog Date:August 1, 2024

This course introduces the Computer Science major to methods for solving classical computer problems through algorithm design. Topics include introduction to structured design, control structures, arrays, object oriented programming, and file processing. Students will learn how to assess and analyze computer problems in a top-down, divide-and-conquer approach that leads to a programming solution. It also includes creating programming plans and detailed design documents from which source code versions of programs will be created.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • choose and apply control structures to solve complex problems.
  • verify empirically the correctness of an algorithm by means of tracing values of variables to validate the accuracy of the solution.
  • develop and create professional, structured programming detailed design documents from which source code can be created.
  • convert values between the binary, decimal, and hexadecimal number systems in order to understand how data are represented in a computer and interpret ASCII values.
  • differentiate roles involved in software development, including developers, analysts, and test engineers.

CISP 310 Computer Architecture and Organization

  • Units:4
  • Hours:54 hours LEC; 54 hours LAB
  • Prerequisite:CISP 360 with a grade of "C" or better
  • Transferable:CSU; UC
  • C-ID:C-ID COMP 142
  • Catalog Date:August 1, 2024

This course is an introduction to computer architecture using assembly language programs. Topics include binary representation of data and instructions, memory addressing modes, subroutines and macros, operating system interrupts, processor architecture, and interfacing with high level languages.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • recognize the computer architecture issues needed to write assembly language code.
  • compare and contrast the binary representation of data and assembly language instructions.
  • create assembly language programs that accept input, perform calculations, and make decisions based on the input, and display an answer.
  • explain the roles of software in the creation, building, and debugging of executable files using assembly language.
  • formulate and implement algorithms to solve complex problems using assembly language.

CISP 360 Introduction to Structured Programming

  • Units:4
  • Hours:72 hours LEC
  • Prerequisite:CISP 300 with a grade of "C" or better
  • Transferable:CSU; UC
  • General Education:AA/AS Area II(b)
  • C-ID:C-ID COMP 112; C-ID COMP 122
  • Catalog Date:August 1, 2024

This course is an introduction to structured programming. The topics covered include: top-down design, input/output considerations, control structures and flow control, variables, constants, the use of libraries, simple to intermediate data structures, functions, and arguments. An introduction into objects will be included.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • organize C/C++ code into modules.
  • create C/C++ programs demonstrating file operations, pointers, and/or structures.
  • create programming problem solutions in C/C++ using selection statements.
  • create programming problem solutions in C/C++ using iteration.
  • create programming problem solutions in C/C++ demonstrating the appropriate use of single and multidimensional array data structures.
  • create programming problem solutions in C/C++ demonstrating the appropriate use of dynamic memory.

CISP 370 Beginning Visual Basic

  • Units:4
  • Hours:72 hours LEC
  • Prerequisite:None.
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course is an introduction to the Visual Basic programming language. Students will design Console and Graphical User Interface programs for the Windows environment. Topics include control structures such as simple sequence, decisions, iteration, procedures, events, properties, error handling, form handling, and the use of typical controls such as buttons, textboxes, checkboxes, and listboxes. This course will provide students with a foundation in the use of objects, object libraries, and object-oriented-event-driven programming techniques.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • design and implement a Graphical User Interface (GUI) to act as the interface between Visual Basic code and an end user.
  • create source code, debug programs, and execute applications using the Visual Studio .NET Integrated Development Environment (IDE).
  • write programs that utilize data from text files, databases, and other sources
  • demonstrate the use of the classes in simple .NET Framework namespaces such as System.Windows.Forms.

CISP 400 Object Oriented Programming with C++

  • Units:4
  • Hours:54 hours LEC; 54 hours LAB
  • Prerequisite:CISP 360 with a grade of "C" or better
  • Transferable:CSU; UC
  • General Education:AA/AS Area II(b)
  • C-ID:C-ID COMP 122
  • Catalog Date:August 1, 2024

This course is an introduction to object-oriented programming using the C++ programming language. This course is designed to enhance students' abilities to implement object-oriented programs and to further develop programming proficiency. Detailed topics include classes, storage class and scope, encapsulation, polymorphism, inheritance, function overloading and overriding, virtual functions, operator overloading, templates, exception handling, stream I/O, file processing, and the Standard Template Library. Also covered are introductions to Graphical User Interface (GUI) development using class libraries, and object oriented design methodology.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • develop skills in object-oriented programming techniques using C++.
  • use the programming language through coding, running, and testing programs.
  • demonstrate an understanding of programming vocabulary and concepts.
  • apply appropriate coding format and documentation standards to written programs.

CISP 401 Object Oriented Programming with Java

  • Units:4
  • Hours:54 hours LEC; 54 hours LAB
  • Prerequisite:CISP 360 with a grade of "C" or better
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course is an introduction to Object Oriented Programming using the Java language. Topics include: objects, classes, UML, function overloading, inheritance, static and dynamic class relationships, polymorphism, components, graphical user interfaces, event driven programming, class associations, interfaces, error handling, threads, file I/O, testing and debugging. This provides the student with a well rounded background in Java and is good preparation for advanced topics.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • design and implement object-oriented software applications using Unified Modeling Language (UML) and the Java language.
  • design and implement reusable software components using inheritance, containment, or polymorphism (abstract classes, interfaces).
  • design and implement event driven Graphical User Interface (GUI) applications, and console applications using Java.
  • utilize successfully Java resources such as files, threads, sockets, string processing, and simple database access.

CISP 405 Object Oriented Programming using C# on Visual Studio .NET

  • Units:4
  • Hours:72 hours LEC
  • Prerequisite:CISP 360 or 370 with a grade of "C" or better
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course is an introduction to the C# programming language using Visual Studio.NET. Topics include the Visual Studio .NET Integrated Development Environment (IDE), object oriented programming concepts, and various .NET technologies. Students will develop programs for the Windows desktop and Web browsers (ASP.NET), as well as explore other .NET technologies such as Web Services, Windows Services, and .NET Remoting.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • demonstrate proficiency in using the Visual Studio .NET integrated development environment to develop Windows desktop Graphical User Interface (GUI) and Web browser applications.
  • define and show how to use typical Visual Basic programming concepts such as control structures, properties, methods, events, threads, arrays, abstract data types, object libraries, and simple database access.
  • utilize structured exception handling mechanisms, create custom exception types, handle exceptions, and raise exceptions in property procedures.
  • implement a simple N-Tier architecture using compiled binary components and several of the following .NET technologies: Web Services, Windows Services, and .NET Remoting.

CISP 407 Programming in Python

  • Units:4
  • Hours:54 hours LEC; 54 hours LAB
  • Prerequisite:CISP 360 with a grade of "C" or better
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

This course provides an introduction to programming with Python. It is designed to enhance students’ abilities to implement programs in Python. Topics include input/output considerations, decision structures and flow control, functions, file processing, and data structures. An introduction to objects will be included.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • understand the Python language and how to apply Python syntax, documentation, and modules.
  • utilize modular design and libraries in the development of algorithms to create solutions to computing problems.
  • utilize and understand the use of assignment statements, conditional statements, loops, function calls and sequences. Be able to design, code, and test small and complex Python programs.
  • solve classical programming problems that includes searching and sorting using Python.
  • describe the concepts of object-oriented programming as used in Python.

CISP 430 Data Structures

  • Units:4
  • Hours:54 hours LEC; 54 hours LAB
  • Prerequisite:CISP 400 with a grade of "C" or better
  • Transferable:CSU; UC
  • C-ID:C-ID COMP 132
  • Catalog Date:August 1, 2024

This is a course in data structures for computer science. Topics include time complexity analysis and big-O notation, searching and sorting, linked lists, stacks, queues, priority queues, lists, binary trees, B-trees, AVL trees, splay trees, graphs, and hash tables. Analysis of algorithms including mergesort, quicksort, heapsort. Graph theory, including shortest paths, topological sort, depth-first search, minimum spanning tree. If time permits, any of the following topics: tries, Huffman codes, branch and bound, Fibonacci heaps, critical path analysis, Open Shortest Path first (OSPF), and basic encryption algorithms.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • analyze algorithms using Big-O Notation.
  • choose appropriate data structures and algorithms.
  • discuss tradeoffs among data structures.
  • solve and implement complex programming tasks.

CISP 440 Discrete Structures for Computer Science

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:CISP 360 and MATH 370 with grades of "C" or better, or placement through the assessment process.
  • Transferable:CSU; UC
  • General Education:AA/AS Area II(b)
  • Catalog Date:August 1, 2024

This course is an introduction to the essential discrete structures used in Computer Science, with emphasis on their applications. Topics to be covered include: binary number representation and arithmetic, sets, relations, functions, formal propositional logic and proofs, digital logic and combinational circuits, finite state machines, regular expressions and formal grammars. Students will implement programs to illustrate principles of discrete structures.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • compare and analyze the fundamental aspects of computer arithmetic including real and negative number binary representation and arithmetic algorithms at the binary level.
  • describe the fundamentals of discrete sets, relations, sequences, strings, and functions.
  • analyze various methods of tree and graph traversals; examine graph and tree algorithms and their application to solving practical problems.
  • analyze and assess fundamental digital logic circuits utilizing Boolean algebra, logic gates, combinational circuits and circuit minimization.
  • explain the basic notions of logical proofs, conditional propositions, logical equivalence, quantifiers, and mathematical induction.
  • understand the concepts of Linear Recurrences, Fibonacci numbers, Dependent (Bayes) probability, Independent (binomial) probability, Pascal's Triangle, the Binomial theorem, Pascal's Identity, and the Master Theorem.
  • design finite state machines, regular expressions, and formal grammars.

CISP 454 Introduction to Software Testing

  • Units:3
  • Hours:36 hours LEC; 54 hours LAB
  • Prerequisite:CISP 400 or 401 with a grade of "C" or better; or object oriented programming industry experience.
  • Transferable:CSU; UC
  • Catalog Date:August 1, 2024

Students will learn and apply industry standard processes and methods for analyzing and testing software, reporting defects effectively, and developing and executing test plans for software projects. Students will be exposed to software tools that implement various testing approaches, including test driven development (TDD). Student teams apply what they learn throughout the course on small development projects. This course prepares students for practical work in the software industry by exposing them to the latest approaches and tools. Examples will be presented in Java and C++.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • explain quality assurance and its relationship to verification and validation.
  • compare unit, integration and system testing.
  • use Test Driven Development (TDD) to write a piece of software.
  • design and review test cases and analyze the results.

CISP 499 Experimental Offering in Computer Information Science - Programming

  • Units:0.5 - 4
  • Prerequisite:None.
  • Transferable:CSU
  • Catalog Date:August 1, 2024

This is the experimental courses description.

Computer Information Science - Security (CISS) Courses

CISS 310 Network Security Fundamentals

  • Units:3
  • Hours:45 hours LEC; 27 hours LAB
  • Prerequisite:CISN 304 with a grade of "C" or better
  • Transferable:CSU
  • C-ID:C-ID ITIS 160
  • Catalog Date:August 1, 2024

This course provides fundamental knowledge for system risk analysis and a workable security policy implementation that protects information assets from potential intrusion, damage, or theft. The required content of the Computing Technology Industry Association (CompTIA) Security+ certification exam is covered.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • describe the fundamental principles of information systems security.
  • define the concepts of threat, evaluation of assets, information assets, physical, operational, and information security and how they are related.
  • evaluate the need for the careful design of a secure organizational information infrastructure.
  • perform risk analysis and risk management.
  • determine both technical and administrative mitigation approaches.
  • explain the need for a comprehensive security model and its implications for the security manager or Chief Security Officer (CSO).
  • create and maintain a comprehensive security model.
  • apply security technologies.
  • define basic cryptography, its implementation considerations, and key management.
  • design and guide the development of an organization’s security policy.
  • determine appropriate strategies to assure confidentiality, integrity, and availability of information.
  • apply risk management techniques to manage risk, reduce vulnerabilities, threats, and apply appropriate safeguards/controls.

Computer Information Science - Web (CISW) Courses

CISW 320 Introduction to Web Development

  • Units:3
  • Hours:54 hours LEC
  • Prerequisite:CISC 310 with a grade of "C" or better
  • Transferable:CSU
  • Catalog Date:August 1, 2024

This course introduces fundamental aspects of coding HTML and CSS. Technical aspects of Web development will be included for using text, images, links, objects, and multimedia on Web pages. Open source developer tools and online resources will be introduced. Websites will be managed locally and on a network using effective file management and file transfer protocols. World Wide Web Consortium (W3C) recommended standards will be emphasized using a structured approach in writing validated, adaptive code for multiple devices: cell, tablet, desktop. Students must have access to high-speed internet, necessary hardware, software, and other digital resources.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • write HTML code using the correct syntax and correct structure for a Web page.
  • write CSS code using the correct syntax to control page layout and visual detail for Web pages; use inline, embedded and external styles.
  • analyze existing Websites for style, structure, and usability in multiple browsers and multiple devices including: cell phones, tablets and desktops.
  • develop websites composed of multiple pages demonstrating effective information architecture and site navigation.
  • validate code to meet recommended standards of the World Wide Web Consortium (W3C) for multiple browsers and devices.
  • research and organize online resources to remain current in Web development.
  • examine open source text editors for Web developers.

CISW 400 Client-side Web Scripting

  • Units:4
  • Hours:72 hours LEC
  • Prerequisite:None.
  • Advisory:CISC 310 and CISP 300
  • Transferable:CSU
  • Catalog Date:August 1, 2024

This course emphasizes the creation of dynamic and interactive Web sites using a client-side scripting language such as JavaScript. Topics include the Document Object Model (DOM) that defines structured Web pages, core features of the client-side scripting language, event handling, control of windows and frames, functions, and form validation.

Student Learning Outcomes

Upon completion of this course, the student will be able to:

  • identify dynamic and interactive Web publishing situations appropriate for client-side scripting.
  • manipulate the various components of a Web page as objects in the Document Object Model.
  • analyze Web publishing problems and situations and develop solutions using the client-side scripting language.
  • build functions and utilize event handlers in the client-side scripting language.
  • assemble the core structures, statements, and syntax of the client-side scripting language in order to create dynamic and interactive Web applications.

CISW 499 Experimental Offering in Computer Information Science - Web

  • Units:0.5 - 4
  • Prerequisite:None.
  • Transferable:CSU
  • Catalog Date:August 1, 2024

This is the experimental courses description.

Science, Technology, Engineering, and Mathematics

Science, Technology, Engineering, and Mathematics icon

This program is part of the Science, Technology, Engineering, and Mathematics meta-major.

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