University General Course Catalog 2022-2023 
    
    Jul 05, 2024  
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8. Course Descriptions

Note: Sequencing rules in effect for many Math courses prohibit students from earning credit for a lower numbered Math course after receiving credit for a higher numbered Math course. Sequencing rules are included in the course descriptions of applicable courses.
 

Community Health Sciences
  

  • CHS 754 - Health Informatics Methods

    (3 units)
    Providing students with knowledge and practical skills in public health informatics, focusing on preparing, designing, developing and implementing health information systems.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring - Odd Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. analyze the different methodological consideration and approaches when design and develop a health information system.
    2. apply information technology to access, evaluate, and interpret public health data.
    3. evaluate and apply basic ethical and legal principles pertaining to the collection, maintenance, use and dissemination of epidemiologic data.
    4. apply the statistical software package (SAS) and MS-ACCESS to develop and manage health data systems.


    Click here for course scheduling information. | Check course textbook information
  

  • CHS 755 - Health Policy

    (3 units)
    Introduces public health graduate students to health policy and the policy making process at the federal, state, and local levels in the US. It emphasizes the role of stakeholders as well as the role of evidence and ethics in creating policy.

    Maximum units a student may earn: 3

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. discuss the policy-making process, including the roles of ethics and evidence.
    2. propose strategies to identify stakeholders and build coalitions and partnerships for influencing public health outcomes. describe the legal and ethical bases for public health and health services.
    3. advocate for political, social or economic policies and programs that will improve health in diverse populations.
    4. evaluate policies for their impact on public health and health equity.
    5. communicate audience-appropriate (i.e., non-academic, non-peer audience) public health content, both in writing and through oral presentation.


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  • CHS 756 - Organizational Behavior and Leadership in Health Services

    (3 units)
    Investigates the impact that individuals, groups, structure, and leadership have on behavior within organizations. Application of this knowledge is used for advancing the effectiveness of health services.

    Maximum units a student may earn: 3

    Prerequisite(s): CHS 755 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. compare the organization, structure and function of health care, public health and regulatory systems across national and international settings.
    2. explain basic principles and tools of budget and resource management.
    3. apply leadership and/or management principles to address a relevant issue.
    4. apply negotiation and mediation skills to address organizational or community challenges.
    5. select communication strategies for different audiences and sectors.


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  • CHS 757 - Health Economics

    (3 units)
    This course introduces public health graduate students to principles of health economics. It emphasizes ways in which the production and consumption of health economics differs from traditional microeconomic models. Students will have opportunities to apply the theoretical models to problems occurring in our healthcare system and will learn how to think through these problems like an economist.

    Prerequisite(s): CHS 756 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. analyze economic incentives present in healthcare markets.
    2. examine how healthcare policy can influence economic incentives present in healthcare markets.
    3. apply economic concepts to better understand the production, consumption, and distribution of health.


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  • CHS 758 - Information Systems in Health Services Management

    (3 units)
    Investigates management information systems in health administration/clinical services. Includes electronic medical records, clinical information systems, management and decision-making technologies.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply “systems thinking” for resolving organizational problems.
    2. assess health policy and management issues using appropriate channels and information system technologies.
    3. compare influences of social, organizational and individual factors on the use of information technology by administrative and clinical end users.
    4. relate with users of communication and informatics specialists in the process of design, implementation, and evaluation of health services programs.
    5. appraise information technology for Quality Improvement to assess, evaluate, and interpret health services and patient data.
    6. justify informatics methods and resources as strategic tools to assist communities in understanding health services.
    7. identify informatics and communication methods for Quality Improvement of health services.


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  • CHS 759 - Health Services Finance

    (3 units)
    Presents the fundamentals of healthcare finance for individuals who desire the knowledge and skills necessary for management positions in healthcare organizations and related businesses.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. analyze financial data to inform decision making in a health care organization.
    2. apply principles of strategic planning in developing a business plan.
    3. develop and present a report on the financial status of a health care organization.


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  • CHS 761 - Public Health Law

    (3 units)
    An exploration of legal and ethical issues in the practice of public health. Reviews the legal foundations of the government’s public health powers and examines the tension between public health activities and individual civil liberties, property rights, commercial speech, and other legally protected interests as well as laws designed to regulate behavior.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall, Spring, and Summer

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. distinguish methods of ensuring community health safety and preparedness through review and analysis of public health law.
    2. apply basic principles of ethical analysis to issues of public health practice and policies.
    3. demonstrate leadership skills for building partnerships that are necessary for the creation and application of public health law and policy.


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  • CHS 762 - Public Health Information Systems and Data Management

    (3 units)
    Focuses on public health information systems and management of public health data.

    Grading Basis: Graded
    Units of Lecture: 3
    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. utilize information technology to access, evaluate, and interpret public health data.
    2. evaluate legal and ethical principles in the use of information technology in public health settings.
    3. manage public health data using statistical software.


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  • CHS 765 - Survival Analysis for Public Health

    (3 units)
    Covers clinical trials and survival analysis and applied methods for time-to-event data including the Kaplan-Meier estimator, (Stratified) Cox regression, Accelerated Failure Time model, recurrent event and competing risk survival analysis.

    Maximum units a student may earn: 3

    Prerequisite(s): CHS 703  or CHS 780 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. develop and apply statistical methods appropriate for time-to-event data.
    2. judge and design statistical models to investigate mediation, confounding, interaction, and effect modification in the context of epidemiologic research.
    3. evaluate, justify, and apply appropriate methodological and analytical approaches to address public health research questions.
    4. manage and analyze data using classic and modern approaches appropriate for various study designs using software packages such as SAS, R, STATA, SPlus, and WinBUGS.
    5. interpret results from statistical analyses of epidemiologic studies.
    6. justify and apply statistical theory and methodology in public health and medical research.


    Click here for course scheduling information. | Check course textbook information
  

  • CHS 766 - Public Health Data Programming

    (3 units)
    Introduction to the SAS and R statistical software applications. Hands on computer lab sections provide students skills and first-hand experience in public health data analysis and data management.

    Grading Basis: Graded
    Units of Lecture: 2
    Units of Laboratory/Studio: 1
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. manage and analyze data using classic and modern approaches appropriate for various study designs using software packages such as SAS, R, STATA, SPlus, and WinBUGS.
    2. interpret results from statistical analyses of epidemiologic studies.
    3. formulate appropriate sampling strategies.
    4. defend analytical models and the results from statistical inferences to diverse audiences trough written and oral presentations.


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  • CHS 780 - Biostatistics in Public Health

    (3 units)
    Introduction to the underlying principles of biostatistics and a variety of statistical applications in public health research.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. analyze quantitative data using biostatistics.
    2. interpret results of data analysis for public health research, policy or practice.
    3. apply specific biostatistical methodologies in the context of a broader public health research framework.


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  • CHS 782 - Analysis of Categorical Data

    (3 units)
    Introduction to theory and methods for the analysis of categorical data including analysis of contingency tables, chi-square and exact tests and logistic models.

    Prerequisite(s): CHS 703  with at least an “A”.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. evaluate, justify, and apply appropriate methodological and analytical approaches to address public health research questions .
    2. manage and analyze data using classic and modern approaches appropriate for various study designs using software packages such as SAS, R, STATA, SPlus, and WinBUGS.
    3. interpret results from statistical analyses of epidemiologic studies.
    4. defend analytical models and the results from statistical analyses to diverse audiences through written and oral presentations.
    5. justify and apply statistical theory and methodology in public health and medical research.


    Click here for course scheduling information. | Check course textbook information
  

  • CHS 784 - Conduct and Analysis of Clinical Trials

    (3 units)
    Issues involved in the design, conduct, analysis, and interpretation of survival studies and randomized controlled trials of health interventions.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring - Odd Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. analyze the purposes, strengths, and weaknesses of various study designs. 
    2. assess the impact of bias and heterogeneity in analytic studies.
    3. implement data management techniques using SAS or other statistical software. 
    4. construct epidemiologic models using statistical programming.


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  • CHS 786 - Biostatistical Analysis in Cohort Studies

    (3 units)
    Principles and methods of biostatistics in cohort studies.

    Prerequisite(s): CHS 703 ; CHS 780 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. evaluate, justify, and apply appropriate methodological and analytical approaches to address public health research questions.
    2. manage and analyze data using classic and modern approaches appropriate for various study designs using software packages such as SAS, R, STATA, SPlus, and WinBUGS.
    3. interpret results from statistical analyses of epidemiologic studies.
    4. Students will be able to defend analytical models and the results from statistical analyses to diverse audiences through written and oral presentations.
    5. justify and apply statistical theory and methodology in public health and medical research.


    Click here for course scheduling information. | Check course textbook information
  

  • CHS 788 - Data Science and Statistical Computation in Public Health

    (3 units)
    An introductory-level course in statistical learning and data mining. This course will cover a basic concept of data mining and techniques used in data mining. Students will learn the general concepts of computation statistics with public health application.

    Prerequisite(s): CHS 780 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. assess the strengths and shortcomings of various methods in data science, machine learning, and computational statistics.
    2. utilize appropriate data science and machine learning methods to solve problems in a given public health context.
    3. manage and analyze large and complex health data, with a particular emphasis on “Big data.”


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  • CHS 789 - Biostatistical Theory

    (3 units)
    An introduction to bio-statistical theory used in public health and biomedical research. The fundamental statistical concepts and methods such as distribution of random variable, central limit theorem, interval estimation, hypothesis testing, maximum likelihood estimation, generalized linear models, EM algorithm, mixed/hierarchical model and GEE will be covered.

    Maximum units a student may earn: 3

    Recommended Preparation: Calculus II; an introductory biostatistics course.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply probability theory to important public health and biomedical problems.
    2. apply the properties of random sample to interval estimation and hypothesis testing.
    3. apply maximal likelihood theory in public health and biomedical research.


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  • CHS 791 - Seminar in Public Health

    (1 to 3 units)
    Intensive study and discussion of selected areas in public health.

    Maximum units a student may earn: 9

    Grading Basis: Graded
    Units of Lecture: 1 to 3
    Offered: Every Fall, Spring, and Summer

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. critically evaluate and synthesize scientific literature.
    2. apply ethical principles pertaining to the collection, maintenance, use, and dissemination of public health data.
    3. effectively defend research methodology and findings through concise scientific writing and oral presentations.
    4. demonstrate theoretical knowledge about the influence of diversity and social determinants on health.


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  • CHS 793 - Readings in Public Health

    (1 to 3 units)
    Recent professional literature in public health.

    Maximum units a student may earn: 9

    Grading Basis: Graded
    Offered: Every Fall - Even Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. read and critically evaluate relevant scientific literature in the specific topic area of the section taken.
    2. articulate in writing or verbally and critically analyze differences between strategies reported in the literature.
    3. describe factors that affect health of individuals and populations from an ecological perspective.
    4. discuss public health ethical considerations in the specific topic area of the section taken.


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  • CHS 794 - Professional Paper

    (1 to 6 units)
    This course is required for all students who wish to earn a M.S. in Biostatistics using the Option B, which requires the writing of a professional paper of a quality suitable for publication in a peer-reviewed journal.

    Maximum units a student may earn: 6

    Prerequisite(s): CHS 703 ; CHS 712 ; CHS 753 ; CHS 780 ; CHS 782 ; CHS 788 ;  6 additional units in graduate-level CHS courses.

    Grading Basis: Satisfactory/Unsatisfactory
    Offered: Every Fall, Spring, and Summer

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. formulate a research question or identify an area of inquiry in biostatistics that is significant and timely.
    2. analyze and synthesize a body of literature to address a question or area of inquiry.
    3. prepare a written document that effectively articulates the results and implications of a comprehensive analysis and synthesis of scholarly literature.
    4. effectively present and defend the findings of their professional paper.


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  • CHS 795 - Comprehensive Examination

    (1 unit)
    Course is used by graduate programs to administer comprehensive examinations either as an end of program comprehensive examination or as a qualifying examination for doctoral candidates prior to being advanced to candidacy.

    Grading Basis: Satisfactory/Unsatisfactory
    Units of Independent Study: 1
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. read and critically evaluate relevant scientific literature in the specific topic area.
    2. articulate in writing or verbally and critically analyze differences between strategies reported in the literature.
    3. summarize current research and critically review the literature pertaining to a research project.
    4. demonstrate the ability to organize and write summary and background sections of a proposal through extensive readings of the primary literature, instruction, discussion, and analysis.


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  • CHS 796 - MPH Capstone

    (3 units)
    Required of all MPH students, this culminating experience requires students to synthesize and integrate foundational and concentration competencies through professional development, a professional paper, and a final presentation. This course is cross-listed with MED 695  for medical students. (CHS 796 and MED 695  are cross-listed; credit may be earned in one of the two.)

    Maximum units a student may earn: 3

    Prerequisite(s): CHS 798 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate audience-appropriate (i.e., non-academic, non-peer audience) public health content, both in writing and through oral presentation.
    2. interpret results of data analysis for public health research, policy or practice.
    3. critically evaluate health-science manuscripts, both published and unpublished.


    Click here for course scheduling information. | Check course textbook information
  

  • CHS 797 - Thesis

    (1 to 6 units)
    Grading Basis: Graded
    Units of Independent Study: X
    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. articulate in writing or verbally and critically analyze differences between strategies reported in the literature.
    2. summarize current research and critically review the literature pertaining to a research project.
    3. develop concise research proposals.
    4. carry out an advanced, independent research project on a chosen topic.
    5. discuss research results in the context of the scientific literature.
    6. communicate and defend the results of the thesis research in writing and in oral presentation.
    7. articulate and follow ethical principles in a scientific context, including professional standards of laboratory practice, the communication of literature research without plagiarism, the crediting of collaborators and standards for co-authorship, and principles of intellectual property.


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  • CHS 798 - Field Studies in Public Health

    (1 to 3 units)
    Supervised field experience in health and wellness settings.

    Maximum units a student may earn: 6

    Grading Basis: Graded
    Units of Internship/Practicum: 1 to 3
    Offered: Every Fall, Spring, and Summer

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply negotiation and mediation skills to address organizational or community challenges.
    2. communicate audience appropriate (i.e., non-academic, nonpeer audience) public health content, both in writing and through oral presentation.
    3. integrate perspectives from other sectors and/ or professions to promote and advance population health.


    Click here for course scheduling information. | Check course textbook information
  

  • CHS 799 - Dissertation

    (1 to 24 units)
    Grading Basis: Graded
    Units of Independent Study: X
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. critically evaluate and synthesize scientific literature.
    2. develop original research hypotheses and research questions that will advance public health knowledge.
    3. evaluate, justify, and apply appropriate methodological and analytical approaches to address public health research questions.
    4. examine ethical principles pertaining to the collection, maintenance, use, and dissemination of public health data.
    5. defend analytical models and the results from statistical analyses to diverse audiences through written and oral presentations.


    Click here for course scheduling information. | Check course textbook information
  

  • CHS 899 - Graduate Advisement

    (1 to 4 units)
    Provides access to faculty for continued consultation and advisement. No grade is filed and credits may not be applied to any degree requirements. Limited to 8 credits (2 semester) enrollment. For non-thesis master’s degree students only.

    Maximum units a student may earn: 8

    Grading Basis: Satisfactory/Unsatisfactory
    Units of Independent Study: X
    Student Learning Outcomes
    Upon completion of this course, students will be able to:


    Click here for course scheduling information. | Check course textbook information

Computer Engineering
  

  • CPE 201 - Digital Design

    (3 units)
    Fundamentals of digital design. Topics include: number bases, binary arithmetic, Boolean logic, minimizations, combinational and sequential circuits, registers, counters, memory, programmable logic devices, register transfer.

    Corequisite(s): CS 135 .

    Grading Basis: Graded
    Units of Lecture: 2
    Units of Laboratory/Studio: 1
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 301 - Embedded Systems Design

    (3 units)
    Embedded systems design and applications. Field Programmable gate arrays, microcontroller architecture, memory and I/O decoding, timers, interrupt systems, analog to digital converters.

    Prerequisite(s): CPE 201  with a “C” or better; CSE majors/minors: CS 219  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 2
    Units of Laboratory/Studio: 1
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. communicate effectively in a variety of professional contexts, with a range of audiences.
    3. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 400 - Computer Communication Networks

    (3 units)
    ISO model, protocol layers, circuit/packet switching, sockets, reliable transport, congestion control, routing, addressing, switching, multiple access, error correction, coding, and digital modulation.

    Corequisite(s): CS 446 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
    4. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 401 - Computer Network Systems

    (3 units)
    Packet switching, routing, congestion control, network layer, internet, transport layer, sessions, FTP, telnet, rlogin, SMTP, NFS, NetBIOS, WWW, security, data compression.

    Prerequisite(s): CPE 400 ; CS 365 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 406 - Real Time Computing Systems

    (3 units)
    Principles of real time computing with applications to process control and laboratory data acquisition. Introduction to real time languages and operating systems. A number of computing projects are to be completed for credit using laboratory hardware and software.

    Prerequisite(s): CPE 301 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 411 - Digital Computer Architecture and Design

    (3 units)
    Fundamental principles of computer architecture and organization. Topics include performance evaluation, memory, input/output, computer arithmetic, instruction sets, processors, RISC, superscalar architectures, control unit.

    Prerequisite(s): CPE 301 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring - Even Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. communicate effectively in a variety of professional contexts, with a range of audiences.
    3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 470 - Autonomous Mobile Robots

    (3 units)
    Design, implementation and programming of autonomous mobile robots; sensors, effectors, basic control theory, fundamental elements of mobile robot control, introduction to advanced topics, illustrations of state-of-the-art. Teamwork: final project tested in a robot contest.

    Prerequisite(s): CS 302  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.


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  • CPE 471 - Advanced Robotics

    (3 units)
    Study and apply research methods commonly used in mobile robotics research. Understand robotic sensing, localization, navigation, perception, and control. Advanced topics in multi-robot systems.

    Prerequisite(s): CS 302  with a “C” or better; STAT 352  or STAT 461 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 481 - Embedded Games Development

    (3 units)
    Computer game development with emphasis on embedded systems and game consoles with fixed resources. Evolution of video display, computer sound, and game i/o technologies.

    Prerequisite(s): CPE 301 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 491 - Topics of Computer Engineering

    (1 to 3 units)
    Topics which are not covered in regular course offerings.

    Maximum units a student may earn: 6

    Prerequisite(s): CS 302  with a “C” or better.

    Grading Basis: Graded
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 493 - Directed Study in Computer Engineering

    (1 to 3 units)
    Intensive study of a special problem in computer engineering.

    Maximum units a student may earn: 6

    Prerequisite(s): CS 302  with a “C” or better.

    Grading Basis: Graded
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 494 - Internship in Computer Engineering

    (1 to 3 units)
    Individual internships in industry are arranged with appropriate companies. Written report is required upon completion of the work.

    Maximum units a student may earn: 3

    Prerequisite(s): CS 302  with a “C” or better.

    Grading Basis: Satisfactory/Unsatisfactory
    Offered: Every Fall, Spring, and Summer

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 600 - Computer Communication Networks

    (3 units)
    ISO model, protocol layers, circuit/packet switching, sockets, reliable transport, congestion control, routing, addressing, switching, multiple access, error correction, coding, and digital modulation.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
    4. acquire and apply new knowledge as needed, using appropriate learning strategies.
    5. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 601 - Computer Network Systems

    (3 units)
    Packet switching, routing, congestion control, network layer, internet, transport layer, sessions, FTP, telnet, rlogin, SMTP, NFS, NetBIOS, WWW, security, data compression.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 606 - Real Time Computing Systems

    (3 units)
    Principles of real time computing with applications to process control and laboratory data acquisition. Introduction to real time languages and operating systems. A number of computing projects are to be completed for credit using laboratory hardware and software.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.
    3. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 611 - Digital Computer Architecture and Design

    (3 units)
    Fundamental principles of computer architecture and organization. Topics include performance evaluation, memory, input/output, computer arithmetic, instruction sets, processors, RISC, superscalar architectures, control unit.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring - Even Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. communicate effectively in a variety of professional contexts, with a range of audiences.
    3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
    4. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 670 - Autonomous Mobile Robots

    (3 units)
    Design, implementation and programming of autonomous mobile robots; sensors, effectors, basic control theory, fundamental elements of mobile robot control, introduction to advanced topics, illustrations of state-of-the-art. Teamwork: final project tested in a robot contest.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.
    3. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 671 - Advanced Robotics

    (3 units)
    Study and apply research methods commonly used in mobile robotics research. Understand robotic sensing, localization, navigation, perception, and control. Advanced topics in multi-robot systems.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
    3. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 681 - Embedded Games Development

    (3 units)
    Computer game development with emphasis on embedded systems and game consoles with fixed resources. Evolution of video display, computer sound, and game i/o technologies.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.
    3. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 691 - Topics of Computer Engineering

    (1 to 3 units)
    Topics which are not covered in regular course offerings.

    Maximum units a student may earn: 6

    Grading Basis: Graded
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 693 - Directed Study in Computer Engineering

    (1 to 3 units)
    Intensive study of a special problem in computer engineering.

    Maximum units a student may earn: 6

    Grading Basis: Graded
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 694 - Internship in Computer Engineering

    (1 to 3 units)
    Individual internships in industry are arranged with appropriate companies. Written report is required upon completion of the work.

    Maximum units a student may earn: 3

    Grading Basis: Graded
    Offered: Every Fall, Spring, and Summer

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 795 - Comprehensive Examination

    (3 units)
    Course is used by graduate programs to administer comprehensive examinations either as an end of program comprehensive examination or as a qualifying examination for doctoral candidates prior to being advanced to candidacy.

    Grading Basis: Satisfactory/Unsatisfactory
    Units of Independent Study: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.
    2. design and conduct experiments as well as to analyze, interpret, apply, and disseminate the data.
    3. understand research methodology.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 796 - Professional Paper

    (3 units)
    Grading Basis: Satisfactory/Unsatisfactory
    Units of Independent Study: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.
    2. design and conduct experiments as well as to analyze, interpret, apply, and disseminate the data.
    3. understand research methodology.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 797 - Thesis

    (1 to 6 units)
    Grading Basis: Graded
    Units of Independent Study: X
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.
    2. design and conduct experiments as well as to analyze, interpret, apply, and disseminate the data.
    3. understand research methodology.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 799 - Dissertation

    (1 to 24 units)
    Grading Basis: Graded
    Units of Independent Study: X
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.
    2. design and conduct experiments as well as to analyze, interpret, apply, and disseminate the data.
    3. understand research methodology.


    Click here for course scheduling information. | Check course textbook information
  

  • CPE 899 - Graduate Advisement

    (1 to 4 units)
    Provides access to faculty for continued consultation and advisement. No grade is filed and credits may not be applied to any degree requirements. Limited to 8 credits (2 semester) enrollment. For non-thesis master’s degree students only.

    Maximum units a student may earn: 8

    Grading Basis: Satisfactory/Unsatisfactory
    Units of Independent Study: X
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.
    2. design and conduct experiments as well as to analyze, interpret, apply, and disseminate the data.
    3. understand research methodology.


    Click here for course scheduling information. | Check course textbook information

Computer Science
  

  • CS 105 - Introduction To Computing

    (3 units)
    Introduction to essential concepts and practices in computing. Design, assemble, and operate basic computer hardware and software in a collaborative environment.

    Grading Basis: Graded
    Units of Lecture: 2
    Units of Laboratory/Studio: 1
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. communicate effectively in a variety of professional contexts, with a range of audiences.
    3. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    4. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.


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  • CS 135 - Computer Science I

    (3 units)
    Introduction to modern problem solving and programming methods. Emphasis is placed on algorithm development. Introduction to procedural and data abstraction, emphasizing design, testing, and documentation.

    Prerequisite(s): MATH 127  or MATH 128  or MATH 181  or MATH 182  or ACT Math score of 28 or SAT Math score of 650 or Accuplacer QAS 276 and AAF 285 or Business major and MATH 176 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall, Spring, and Summer

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.
    3. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 151 - Introduction to Cybersecurity

    (3 units)
    Introduction to fundamental concepts of cybersecurity, common cybersecurity vulnerabilities and threats, and techniques and tools for detecting and defending against cyber-attacks.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 202 - Computer Science II

    (3 units)
    Emphasis on problem solving and program development techniques. Typical numerical and non-numerical problems are examined. Design, implementation, and abstraction principles of elementary data structures.

    Prerequisite(s): CS 135  with a “C” or better. Corequisite(s): ENGR 100  for Computer Science and Engineering majors. Recommended Preparation: Basic program design, understanding and ability to use functions, declarations, single and multidimensional arrays, basic stream I/O.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. apply computer science theory and software development fundamentals to produce computing-based solutions.
    3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 219 - Computer Organization

    (3 units)
    Introduction to organization and integration of computer components. Topics include: computer abstractions and performance, arithmetic operations, instruction set architecture, assembly programming, datapath, pipelining, memory hierarchy, I/O, and parallel architectures.

    Prerequisite(s): CPE 201  with a “C” or better; CS 202  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 252 - Digital Forensics Fundamentals

    (3 units)
    Introduction to the basic computer and networking, forensic process, digital evidence collection, preserving the evidentiary chain, cybercrime statutes, and the legal aspects of search and seizure.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 302 - Data Structures

    (3 units)
    Data structures and algorithms fundamental to computer science; abstract data-type concepts; measures of program running time and time complexity; algorithm analysis and design techniques.

    Prerequisite(s): CS 202  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    3. communicate effectively in a variety of professional contexts, with a range of audiences.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 326 - Programming Languages, Concepts and Implementation

    (3 units)
    An overview of programming languages; features, structures, and implementation; examples taken from various programming paradigms. Introduction to formal specifications of languages.

    Prerequisite(s): CS 302  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 328 - Fundamentals of Game Design

    (3 units)
    Fundamental topics related to game design. Topics include: game design requirements, game design principles, evaluation, peer review, prototyping.

    Prerequisite(s): CS 202 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.
    3. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 330 - Design Patterns

    (3 units)
    Introduction to design patterns: Strategy, Observer, Factory, Singleton, Command, Adapter, Faade, Template Method, Iterator, Composite, State, Proxy. Object Oriented design principles, Java/UML.

    Prerequisite(s): CS 202  with a “C” or better. 

    Grading Basis: Graded
    Units of Lecture: 3
    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 365 - Mathematics of Computer Science

    (3 units)
    Computing related mathematical constructs and concepts. Topics covered include: propositional/predicate logic, proofs, sets functions algorithms, matrices, sequences, induction, recursion, combinatorics, probability, relations, graphs.

    Prerequisite(s): CS 202  with a “C” or better; MATH 182  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply computer science theory and software development fundamentals to produce computing-based solutions.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 381 - Game Engine Architecture

    (3 units)
    Introduction to the technical elements of modern videogame and the pipeline for assembling them, plus issues of interface design, quality assurance, and business practice.

    Prerequisite(s): CS 202 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 415 - Parallel Computing

    (3 units)
    Parallel algorithms and architectures. Taxonomy of systems, SIMD, MIMD, systolic arrays. Parallel languages and programming paradigms. Applications using a multiple processor parallel network.

    Prerequisite(s): CS 302  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring - Odd Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 420 - Human-Computer Interaction

    (3 units)
    Usability goals, design principles, design processes, prototyping, interface metaphors, interaction styles, interaction devices, software tools, evaluation paradigms and techniques, user manuals, collaborative work, information visualization.

    Prerequisite(s): CS 302 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall - Odd Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate effectively in a variety of professional contexts, with a range of audiences.
    2. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    3. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 422 - Introduction to Machine Learning

    (3 units)
    Machine learning studies representations and algorithms that allow machines to improve their performance on a task from experience. This is a broad overview of existing methods for ML. Emphasis is given to practical aspects of ML.

    Pre-requisite(s): CS 302   with a “C” or better; MATH 330  with a “C” or better. Recommended Preparation: Calculus, Probability and Statistics.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate effectively in a variety of professional contexts, with a range of audiences.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 425 - Software Engineering

    (3 units)
    Software processes, project management, software requirements, system models, architectural design, detailed design, user interface design, implementation, integration, verification, validation, testing, evolution, rapid development, software tools.

    Prerequisite(s): CS 446  with a “C” or better; CSE major; Junior or Senior standing.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.
    3. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 426 - Senior Projects in Computer Science

    (3 units) CO14
    Supervised group or team projects with emphasis on implementation of engineered design.

    Prerequisite(s): CSE major; Junior or Senior standing; CS 425  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. communicate effectively in a variety of professional contexts, with a range of audiences.
    3. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    4. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.
    5. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 431 - Introduction to Big Data

    (3 units)
    This course offers an introduction to big data techniques and applications. It covers basic topics like Big Data Overview, Big Data Management, Big Data Modeling, Big Data Analytics, Big Data Tools, and Big Data Applications.

    Prerequisite(s): CS 302  with a “C” or better; STAT 352  or STAT 461  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate effectively in a variety of professional contexts, with a range of audiences.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 433 - Data Intensive Computing

    (3 units)
    This course is a tour through various research topics in cluster computing, grid computing, and cloud computing. This course is geared for senior level undergraduates and graduate students.

    Prerequisite(s): CS 446  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 436 - Big Data Systems

    (3 units)
    This course offers an advanced study of state-of-the-art big data techniques and applications and focuses on the tools and systems for big data analytics.

    Prerequisite(s): CS 302  with a “C” or better; STAT 352  or STAT 461  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate effectively in a variety of professional contexts, with a range of audiences.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 442 - Cloud Computing

    (3 units)
    Cloud characteristics and security issues. Service, deployment and billing models. Hypervisors and virtualization. Data replication and persistence approaches. Administration and development of clouds.

    Prerequisite(s): CPE 400 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 445 - Internet Security

    (3 units)
    An introduction to the topics related to fundamentals of computer networks security, network protocols, vulnerabilities, security policy, risk assessment, management, and mechanisms for secure network infrastructures.

    Prerequisite(s): CPE 400 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 446 - Principles of Operating Systems

    (3 units) CO12
    Concurrent processes, interprocess communication, processor management, virtual and real memory management, deadlock, file systems, disk management, performance issues, case studies. Practical experience with UNIX.

    Prerequisite(s): CS 105  or ENGR 100 ; CS 219  with a “C” or better; CS 302  with a “C” or better. Corequisite(s): ENGR 301  (for CSE majors only).

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 447 - Computer Systems Administration

    (3 units)
    Account maintenance, backups, restoration, system configuration, resource allocation and monitoring, network management, peripheral administration, emphasis on UNIX systems.

    Prerequisite(s): CS 446 .

    Grading Basis: Graded
    Units of Lecture: 3
    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 450 - Fundamentals of Integrated Computer Security

    (3 units)
    Network security, database and system security, access control, policy and ethics development, attacks, and counter attack measures, security tools and malicious code, current trends and research. Projects completed in a high level language.

    Prerequisite(s): CS 446 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 453 - Mobile Computing Security and Privacy

    (3 units)
    Emerging topics on security and privacy in mobile computing, including misbehavior detection in wireless networks, wireless routing privacy, malicious access point detection, cognitive authentication, privacy protection.

    Prerequisite(s): CPE 400  or CPE 401 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate effectively in a variety of professional contexts, with a range of audiences.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 454 - Reliability and Security of Computing Systems

    (3 units)
    Emphasis on cryptography (encryption, hash functions and message authentication), hardware-based security and trust, and hardware/software fault tolerance.

    Prerequisite(s): CS 219 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 455 - Mobile Sensor Networks

    (3 units)
    Emerging topics on mobile sensor networks (MSNs) research. Study and apply research methods commonly used in MSNs. Understand basic sensor/robot localization, navigation, fusion and control techniques.

    Prerequisite(s): CS 326 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 456 - Automata and Formal Languages

    (3 units)
    Fundamental concepts of computation. Relationship between grammars, languages and machines, emphasizing regular and context free languages, finite state acceptors and Turing machines. Complexity and computability.

    Prerequisite(s): CS 302  with a “C” or better; CS 365  with a “C” or better; MATH 283 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. apply computer science theory and software development fundamentals to produce computing-based solutions.
    2. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 457 - Database Management Systems

    (3 units)
    An overview of existing systems; physical data organization; relational, network and hierarchical models; data manipulation languages, data definition languages; database protection; database application using INGRES.

    Prerequisite(s): CS 302 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 458 - Introduction to Data Mining

    (3 units)
    Introduction of the basic concepts, representative algorithms, and state-of-art techniques of data mining. We will examine the present techniques and theories behind them, and explore new techniques for real world data mining applications.

    Prerequisite(s): CS 202  with a “C” or better; MATH 330 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate effectively in a variety of professional contexts, with a range of audiences.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 460 - Compiler Construction

    (3 units)
    Introduction to compiler writing techniques, grammars for syntax definition, use of compiler writing tools, compilers for simple languages, case studies of actual compilers.

    Prerequisite(s): CS 326 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring - Even Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate effectively in a variety of professional contexts, with a range of audiences.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 461 - Statistical Methods in Bioinformatics

    (3 units)
    Study and apply computational methods commonly used in biomedical research. Understand different types of biomedical data and appropriate computational and statistical approaches. Advanced topics in sequencing data analysis.

    Prerequisite(s): CS 365  with a “C” or better or STAT 352  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 466 - Numerical Methods I

    (3 units)
    Numerical solution of linear systems, including linear programming; iterative solutions of non-linear equations; computation of eigenvalues and eigenvectors, matrix diagonalization. (CS 466 and MATH 466 are cross-listed; credit may be earned in one of the two.)

    Prerequisite(s): MATH 330 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 467 - Numerical Methods II

    (3 units)
    Numerical differentiation and integration; numerical solution of ordinary differential equations, two point boundary value problems; difference methods for partial differential equations. (CS 467 and MATH 467 are cross-listed; credit may be earned in one of the two.)

    Prerequisite(s): MATH 285 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 474 - Image Processing and Interpretation

    (3 units)
    Image files, thresholding, histograms, convolution, edge detection, segmentation, frequency domain filtering, morphology, registration, combining images.

    Prerequisite(s): CS 202  with a “C” or better; STAT 352  or STAT 461 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall - Odd Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 477 - Analysis of Algorithms

    (3 units)
    Analysis and design of algorithms on sequences, sets, graphs and trees. Geometric, algebraic and numeric algorithms, FFTs, reductions. Parallel algorithms.

    Prerequisite(s): CS 302  with a “C” or better; CS 365  or EE 291 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 479 - Pattern Recognition

    (3 units)
    Pattern recognition systems, statistical methods, discrimination functions, clustering analysis, unsupervised learning, feature extraction and feature processing.

    Prerequisite(s): CS 202  with a “C” or better; STAT 352  or STAT 461 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring - Even Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. communicate effectively in a variety of professional contexts, with a range of audiences.
    3. acquire and apply new knowledge as needed, using appropriate learning strategies.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 480 - Computer Graphics

    (3 units)
    Software, hardware and mathematical tools for the representation, manipulation and display of two- and three dimensional objects: applications of these tools to specific problems.

    Prerequisite(s): CS 302  with a “C” or better; MATH 182  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. communicate effectively in a variety of professional contexts, with a range of audiences.
    3. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 481 - Advanced Computer Game Design

    (3 units)
    The engineering, science, and art of creating advanced computer games. Design and implementation of game components in producing usable and engaging computer games.

    Prerequisite(s): CS 381 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. communicate effectively in a variety of professional contexts, with a range of audiences.
    2. function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline, creating a collaborative and inclusive environment, establishing goals, planning tasks, and meeting objectives.
    3. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 482 - Artificial Intelligence

    (3 units)
    Problem solving, search, and game trees. Knowledge representation, inference, and rule-based systems. Semantic networks, frames, and planning. Introduction to machine learning, neural-nets, and genetic algorithms.

    Prerequisite(s): CS 302 ; CS 365 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Fall - Odd Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 484 - Virtual Reality

    (3 units)
    Students will learn about sensor, display, and computing technology as well as human perceptual and motor processes that underlie virtual reality technology. (CS 484 and PSY 484 are cross-listed; credits may be earned in one of the two.)

    Prerequisite(s): Junior or senior standing.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
    2. recognize professional responsibilities and make informed judgments in engineering and computing practice based on legal and ethical principles, considering the impact of solutions in global, economic, environmental, and societal contexts.
    3. explain the strengths and weaknesses of VR relative to other media platforms or tools.
    4. develop simple VR software applications.
    5. demonstrate knowledge of human perceptual and motor function and its relevance for VR technology.
    6. demonstrate competence with VR technology and knowledge of sensory, display, and computing requirements.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 485 - Computer Vision

    (3 units)
    Principles, design and implementation of vision systems. Camera models and image formation, feature detection, segmentation. Camera calibration, 3-D reconstruction, stereo vision. Introduction to advanced topics.

    Prerequisite(s): CS 302  with a “C” or better.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring - Odd Years

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. design, implement, and evaluate a computing or engineering solution to meet a given set of requirements, with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 486 - Introduction to Convex Optimization

    (3 units)
    This course will introduce basic concepts of convex optimization and algorithms for convex optimization (e.g., Newton’s method, gradient descent methods). We will concentrate on recognizing and solving convex optimization problems that arise in engineering applications. This course would benefit anyone who uses or will use scientific computing or optimization in engineering or related work (e.g., machine learning, robotics, computer graphics, algorithms & complexity, computational geometry).

    Maximum units a student may earn: 3

    Prerequisite(s): CS 202  with a “C” or better; MATH 330 .

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
    2. apply computer science theory and software development fundamentals to produce computing-based solutions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 487 - Fundamentals of Deep Learning

    (3 units)
    Principles, design and implementation of deep learning systems. Topics include statistical machine learning, multi-layer perceptron (MLP) and neural networks, deep neural networks, optimization and learning, convolutional neural networks (CNN), CNN architectures, CNN applications in classification, detection, segmentation, and advanced topics in recurrent networks and generative adversarial networks (GAN).

    Prerequisite(s): CS 302  with “C” or better; MATH 330 . Recommended Preparation: Machine Learning, solid mathematical background and good programming skills.

    Grading Basis: Graded
    Units of Lecture: 3
    Offered: Every Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
    2. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.


    Click here for course scheduling information. | Check course textbook information
  

  • CS 491 - Topics

    (1 to 3 units)
    Selected topics in computer science. May be repeated when course content differs.

    Grading Basis: Graded
    Units of Lecture: X
    Offered: Every Fall and Spring

    Student Learning Outcomes
    Upon completion of this course, students will be able to:
    1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.


    Click here for course scheduling information. | Check course textbook information
 

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