Courses

The course serves as an introduction to the exciting field and vocation of engineering and the value of engineering education. This course includes guest lectures describing various engineering disciplines, team-based introductory projects, community service, and weekly readings that focus on how to be successful as an engineering student. The weekly readings include topics on self-discovery, goal setting, work-life balance, and understanding the teaching/learning process. A course emphasis includes Christian perspectives on purpose, integrity, and service as they relate to the vocation of engineering. This is the first course required of all students considering engineering as a major. Note: This is a required course for Engineering, Computer Science, and Construction Management Majors. Pre- or Co- Requisite: ICS 105. (3 units; Fall)

Introduction to fundamental techniques used in engineering design and analysis. Different models of the design process will be examined. A collaborative team oriented design project will be undertaken. (4 units; Spring)

Engineering is a discipline which requires the effective communication of visual information as part of persuasion or education. Excel (beginning and advanced techniques), and a CAD program will be covered to assist in that process for a real current engineering problem of interest. For example this might include the utilization of solar power in Riverside County to address energy consumption concerns. This course lays the foundation for future courses which have elements of data and information presentation. (3 units; Fall/Spring)

This course addresses the basic elements of the Christian faith in the context of participating in Gods global agenda. Topics include Christian worldview, the Kingdom of God, the gospel of Jesus Christ, the work of the Holy Spirit, the mission of the Church, and the role of prayer. (3 units; Fall/Spring)

Preparation for a lifetime of leadership as an engineer. Small group discussion format, with opportunities for student facilitated discussions. Topics include: leadership in organizations, emotional intelligence, the psychology of small group dynamics and team performance, global perspectives of engineering. Written executive summaries as part of a “4MAT” like response will be required prior to discussion. Prerequisite: Permission of the Department Chair. (1 unit; Spring)

Designed to prepare you for the official internship during your junior summer. Discussion and development of the individual's priorities for their learning contract. Topics include: resume and internship writing, finding an internship, how you will be assessed as an intern, the psychology of the workplace, different types of bosses and working on teams, and the different types of work environment. Junior status or greater is required. (1 unit; Fall)

The first of a two course senior capstone design sequence. Various design topics may be discussed including equipment design, the design of process systems, and economics. Student teams select a project which may involve company sponsorship, and proceed through the design methodology introduced in earlier design classes, incorporating appropriate engineering standards and multiple realistic constraints. Every project has a 'customer' which requires the generation of a customer spec. During the sequence students provide detailed schedules for building a prototype system or designing a process and present weekly progress reports. They also produce technical specifications, undergo a preliminary design review (PDR), and build a working prototype system if appropriate. Prerequisite: EGR 302 or 352. (3 units; Fall)

A continuation of EGR 401. Further development of the project will take place and will involve testing as appropriate. Teams will develop proper documentation for their projects and will appropriately communicate and present the results of their project. A final presentation is given to the public which could include members of the engineering advisory council. The presentation will be recorded and included as a part of students' senior portfolios. Prerequisite: EGR 401. (3 units; Spring)

Students will report on their internship experiences. Each student will submit a written report and give an oral presentation. Students will receive faculty and peer evaluations of their presentations. Prerequisite: Permission of the Department Chair. (1 unit; Fall/Spring)

Algorithms are the heart of any computer software; they define the procedure for accomplishing a data-intensive task. This course establishes terms and methods for talking about algorithms, examines some of the basic algorithms for sorting, searching and other fundamental tasks, and explores more advanced algorithms in bioinformatics and other fields. Prerequisite: EGR 227. (3 units; Fall/Spring)

Introduction to computer science. Covers problem solving methods and algorithm development; modern programming methodologies; and fundamentals of high-level block structured language using C++. Prerequisite: EGR 181 or MAT 115. (3 units; Fall, Spring, & Online)

Overview of the software development process. Includes requirements, design, construction, and testing of software. Software project planning. Analysis, architecture, and design of software systems using UML. Evaluating designs. Implementing designs using appropriate data structures, frameworks, and APIs. Prerequisite: EGR 120 or 121. (3 units; Fall/Spring/Summer)

Fundamental data structures for implementation and analysis. Techniques for solving problems by programming. Analysis for complexity and performance trade-offs. Topics include object oriented design, debugging, abstract data types (ADTs), recursion, big-O notation, interfaces, inheritance, and encapsulation, linked lists, stacks, queues, hash tables, heap, trees, searching, sorting. Prerequisite: EGR 222. (3 units; Fall/Spring)

This course explores issues related to the production and the analysis of imagery and visual representations. Computer graphics are introduced, from basic concepts through rendering and animation. Visualization of data is presented. Computer Vision and Image Processing is presented both mathematically and practically, with an emphasis on creating image manipulation programs in a high-level language. Prerequisite: EGR 227. (3 units; Spring)

Introduction to concepts and considerations of modern compilers and programming languages. Language translation, types and declaration, and abstraction mechanisms are studied. Both functional and object-oriented programming paradigms are explored through examination of several programming languages. Automata, languages and grammar, language processing, computability and complexity theory will be examined in detail. Important topics will be explored using a combination of conceptual work and coding exercises. Prerequisites: EGR 225 and 227. (3 units; Fall)

Introduces the fundamentals of operating systems including processes, memory, scheduling, input/output together with the basics of networking protocols. Prerequisite: EGR 222. (3 units; Spring)

Overview of current database technologies with an emphasis on relational database technology. Introduction to database design, entity relationship diagraming, structured query language, and stored procedures. Prerequisite: EGR 120 or 121. (3 units; Fall)

Introduces students to the organization and architecture of computer systems, beginning with the standard von Neumann model and then moving forward to more recent architectural concepts. Introduction to assembly language programming. Prerequisite: EGR 120 or 121. Pre- or Co- Requisite: EGR 225. (3 units; Fall)

The design and development of data driven web applications. The integration and exploitation of HTML, JavaScript, server-side programming languages and database technology. Prerequisite: EGR 222. (3 units; Fall)

Investigation of mobile operating systems and associated software development environments. Consideration of unique constraints and techniques for creating software designed for mobile devices. Design and development of several mobile applications targeted at the primary mobile operating systems. Prerequisite: EGR 222 (3 units; Fall)

Investigation of modern cloud computing platforms and the practice of creating scalable software solutions that utilize essential cloud computing products like serverless computing, serverless key-value NOSQL databases, cloud storage, publisher/subscriber messaging, identity access and permissions management, machine learning (ML) integration, etc. Prerequisite: EGR 226. (3 units; Spring)

Team design of industrial or self-designed projects. Requires the design and development of a process or product with oral and written reports. Includes a review and analysis of professional papers. Pre- or Co- Requisites: EGR 102 and one of the following: CSC 321, 322, or EGR 305, or both CSC 221 and EGR 325. (3 units; Spring)

Focus on Programming real-time applications on an embedded platform running a real-time operating system (RTOS). Consideration will be given to cross-compiled software development, embedded system debugging, multitasking, real-time scheduling, inter-task communication, software design for deterministic execution time, software performance analysis and optimization, device drivers. Prerequisites: EGR 222 and 329. (3 units; Spring)

This course will provide an overview of the salient math topics most heavily used in the core sophomore-level engineering courses. These include trigonometry, vectors, complex numbers, sinusoids and harmonic signals, systems of equations and matrices, derivatives, integrals, differential equations and Fourier series within the context of an engineering application. These concepts will be reinforced through extensive examples of their use in the core engineering curriculum. Students may only earn credit for either EGR 182 or EGR 182L. Prerequisite: EGR 181 or MAT 115. (4 units; Fall/Spring)

Introduces the foundations of discrete mathematics as they apply to computer science, focusing on providing a solid theoretical foundation for further work. Topics include functions, relations, sets, simple proof techniques, Boolean algebra, propositional logic, digital logic, elementary number theory, and the fundamentals of counting. (3.0 units; Fall)

Basic concepts of analytical geometry, limits and derivatives, differentials and rates, integration, definite and indefinite integrals, differentiation of logarithmic and exponential functions. Prerequisites: MAT 135, 145, EGR 182, or sufficient SAT, ACT or math placement exam scores and appropriate high school mathematics background. (4 units; Fall/Spring)

Vector spaces; matrices, rank and systems of linear equations; linear transformation; similarity and diagonalization theorems; eigenvectors and eigenvalues. Prerequisite: MAT 313, or 245 and EGR 225. (3 units; Spring)

The first semester of a two-semester course providing a systematic development of the theories of probability and statistics. Students learn and use fundamental concepts of probability models, random variables and their distributions, reduction of data, estimation, testing of hypotheses, univariate normal inference, and statistical decision theory. The first semester is required for BA and BS statistics majors of all concentrations. Prerequisites: MAT 245, and one of the following: EGR 120, 121, or STA 144. (3 units; Fall)

Second semester course in a systematic development of the theories of probability and statistics. Topics include analysis of categorical data, multivariate distributions, nonparametric inference, linear models and analysis of variance. As time permits, the theory underlying Markov chain, Monte Carlo, quasi-likelihood, empirical likelihood, statistical functionals, generalized estimating equations, the jackknife, and the bootstrap are addressed. Prerequisite: STA 310. (3 units; Spring)

This course covers topics such as units, vectors, motion (in one, two and three dimensions), Newton's laws of motion, work, kinetic and potential energy, momentum, impulse, collisions, conservation laws, dynamics of rotational motion, equilibrium, gravitation, and periodic motion. Six (6) hours per week of inquiry-based instruction. Additional course fee. Prerequisite: MAT 145 or a B or better in EGR 182. Pre- or Co- Requisite: MAT 245. (4 units; Fall/Spring)

A study of the physiology, morphology, reproduction, and a survey of the plant kingdom, including fungi, algae, liverworts, mosses, ferns, gymnosperms and angiosperms. Emphasis will be placed on the development, reproduction and the relevance of plants to humans. Lecture (3 units) and required laboratory (1 unit). Additional lab fee. (4 units; Spring)

Topics covered include cell structure and function, genetics, reproduction and development of animal systems. Lecture (3 units) and required laboratory (1 unit). Additional lab fee. (4 units; Fall/Spring)

This course is designed for professional nursing and general college students. Included are a general survey of human histology and the study of structure and function of organ systems of the human body, including the integumentary, skeletal, muscular, endocrine, and nervous systems. Structure and function of sensory organs are also included in the course. Should be taken with BIO 153L. (3 units; Fall, Spring, Summer, & Online)

A laboratory experience designed to illustrate and reinforce topics covered in Anatomy and Physiology I. Included is the detailed study of cells, tissues, the structure and function of the skeleton, the muscles, and the nervous and endocrine systems of the human body using laboratory experience and demonstration. Additional lab fee. Pre- or Co- Requisite: BIO 153. (1 unit; Fall, Spring, Summer, & Online)

A survey of Organic and Biochemistry topics with special emphasis on metabolic processes and applications to medicine and health. Should be taken with CHE 112L - Organic and Biochemistry for Health Sciences Lab. Prerequisites: CHE 102, or 115 and 115L. (3 units; Fall/Spring/Summer)

A laboratory experience designed to illustrate and reinforce topics covered in Organic and Biochemistry and introduce students to laboratory experiments and equipment that are foundational to the study of these disciplines. Additional lab fee. Pre- or Co- Requisite: CHE 112. (1 unit; Fall/Spring/Summer)

A study of inorganic chemical systems including properties of atoms, molecules and ions, composition of matter, solutions, stoichiometry, thermochemistry, gas laws, electronic structure of elements, chemical bonding and molecular geometry. Course content is presented at a level required for Chemistry and related science majors. Lecture: 3 units. Prerequisite: CHE 102 or high school chemistry. (3 units; Fall/Spring)

A laboratory experience designed to illustrate and reinforce topics covered in General Chemistry I and introduce students to laboratory practices, experiments and equipment that are foundational to the study of Chemistry. Additional lab fee. Pre- or Co- Requisite: CHE 115. (1 unit; Fall/Spring)

A study of the earth, time, moon, sky, celestial mechanics, solar system, and the sidereal universe. (3 units; Fall)

A study of the laws of physics related to the optics of telescopes. Observational labs, including remotely operating telescopes on mountain tops. Additional lab fee(s). (Field trips may require additional lab fees). Pre- or Co- Requisite: PHY 113. (1 unit; Fall)

This course covers topics such as fluids, temperature and ideal gas, electric charge and field, Gauss' Law, electric potential, capacitance and dielectrics, current, resistance and electromotive force, direct-current circuits, magnetic field and force, Ampere's and Faraday's laws, electromagnetic induction, inductance, alternating current circuits, and electromagnetic waves. Six (6) hours per week of inquiry-based instruction. Additional course fee. Prerequisites: PHY 201 and MAT 245. (4 units; Fall/Spring)

A consideration of the sea as a biological environment, of the biota, and of the interrelationships existing between marine organisms and the physical, chemical, and biological aspects of their environments. The course provides a field and laboratory course emphasizing identification and life histories of marine organisms. Does not meet the science/lab requirement for Liberal Studies waiver. Lecture (3 units) and required laboratory (1 unit). Lab fee: See the Financial Information Section. (4 units; Fall/Spring)

In this course students will integrate and apply concepts from a variety of disciplines such as chemistry, physics, biology, mathematics, etc., to the study of forensic science. The theoretical foundations of common forensic science techniques will be covered along with applications to specific forensic scenarios. Lecture (3 units) and required laboratory (1 unit). Additional lab fee. (4 units; Spring)

This course provides an introduction to the field of Security in computing. Topics include common security standards and policies, cryptography and information security, access controls, attacks and countermeasures, and computer forensics. Prerequisite: EGR 222. (3 units; Spring)

This course provides an in-depth look into the fundamentals of packet-switched network traffic analysis at the network layer and above as applied to problems in traffic engineering, economics, security, etc. The course will explore the design and integration of analytic tools and techniques into the fabric of the network including: spatial and temporal anomaly detection, origin-destination matrix estimation, application mix determination, deep-packet inspection, fingerprinting, intrusion detection and insider threat mitigation. Finally, the course covers active defense and offensive methods reliant on traffic analysis. Contains a lab component. Prerequisite: CSC 431. (3 units; Spring)

This course provides an in-depth look to define the nature and scope of cyber security incident handling services, including intrusion/incident detection, damage control, service continuity, forensic analysis, service/data restoration, and incident reporting. Material covers policy, planning, operations, and technology issues involved in related cyber incident handling plans; i.e., Business Continuity, Disaster Recovery, and Continuity of Operations. Specific incident types addressed include, natural disasters, denial of service, malicious code, malicious misuse of hardware and firmware, unauthorized access, data compromise and inappropriate use, including insider attacks. Emphasis is given to the detection and analysis of infiltration and exfiltration techniques employed during cyber attacks, thus enabling the incident handler to detect low noise attacks, and to deconstruct particularly insidious attacks. Contains a lab component. Prerequisite: CSC 431 (3 units; Fall)

This course provides an advanced course that focuses on key principles of a constructive approach to secure systems. A brief review of operating systems and computer architecture is provided. Major topics include threat characterization and subversion; confinement; fundamental abstractions, principles, and mechanisms, such as reduced complexity, hierarchical relationships, least privilege, hardware protection, resource management and virtualization, software security, secure system composition, mutual suspicion, synchronization, covert and side-channel analysis, secure metadata, secure operational states, usability, and life cycle assurance. Current developments will include advances in security hardware, components, and systems. This course has heavy reliance on software development and implementation. Prerequisite: CSC 431. (3 units; Spring)

Artificial Intelligence (AI) is concerned with the design and analysis of autonomous agents that perceive their environment and make rational decisions. This course introduces the basic definitions and issues in Artificial Intelligence and Machine Learning. Students will create reasoning systems in software and explore their capabilities in dealing with new knowledge. Ethical issues in AI will be presented and examined from a Christian perspective. Prerequisite: EGR 227 (3 units; Spring)

Artificial Intelligence (AI) is concerned with the design and analysis of autonomous agents that perceive their environment and make rational decisions. This course introduces the basic definitions and issues in Artificial Intelligence and Machine Learning. Students will create reasoning systems in software and explore their capabilities in dealing with new knowledge. Ethical issues in AI will be presented and examined from a Christian perspective. Prerequisite: EGR 227 (3 units; Spring)

This course provides an introduction to the field of Security in computing. Topics include common security standards and policies, cryptography and information security, access controls, attacks and countermeasures, and computer forensics. Prerequisite: EGR 222. (3 units; Spring)

This course covers introductory machine learning topics including supervised and unsupervised learning, linear and logistic regression, support vector machines, neural networks (MLPs, CNNs, RNNs, GANs) and more. Coursework includes instruction and programming assignments in algorithmic implementations and high-level library usage. Students also apply machine learning techniques to a unique research project. Prerequisites: EGR 120 or 121, and one of the following: EGR 305, MAT 353, STA 144, 310, or one additional approved statistic course. (3 units; Fall)

The course commences with an examination of the knowledge discovery process. In particular, the introduction equips students with the strategic thinking skills essential to focus on cutting edge data mining techniques that can be applied in a wide variety of settings, e.g., business, engineering, health care, science, etc. Traditional topics include data mining algorithms and implementation issues, advantages and disadvantages of data mining, and examples of knowledge engineering. Current topics such as ubiquitous, distributed, and spatiotemporal geographic data mining will also be explored. This is a practical hands-on course that culminates in a real-world project implemented via open source tools. Prerequisites: EGR 120 or 121, and one of the following: EGR 305, MAT 353, STA 144, 310, or one additional approved statistics course. (3 units; Fall)

Natural language is ubiquitous, e.g., humans speak and write to communicate, to transfer information, and to document knowledge. Natural Language Processing (NLP) is an integral component in countless information systems requiring advanced manipulation of natural language. In this class, students will be introduced to NLP starting with the concept of understanding words in context and the need for natural language processing in the business environment. The discussion continues with a detailed study of words and is a foundational framework supporting phonetics and speech synthesis. Subsequent topics include concepts of how words are grouped together to form unique grammatical units. The last part of the course, explores solving real-world NLP problems and deals with two key areas: corpus building, feature engineering, and application development. Course material is presented via theory-based lectures, group discussion, and practical labs-a culminating research project will be individually crafted. Prerequisites: EGR 120 or 121, and one of the following: EGR 305, MAT 353, STA 144, 310, or one additional approved statistics course. (3 units; Spring)

This course provides an in-depth look into the fundamentals of packet-switched network traffic analysis at the network layer and above as applied to problems in traffic engineering, economics, security, etc. The course will explore the design and integration of analytic tools and techniques into the fabric of the network including: spatial and temporal anomaly detection, origin-destination matrix estimation, application mix determination, deep-packet inspection, fingerprinting, intrusion detection and insider threat mitigation. Finally, the course covers active defense and offensive methods reliant on traffic analysis. Contains a lab component. Prerequisite: CSC 431. (3 units; Spring)

This course provides an in-depth look to define the nature and scope of cyber security incident handling services, including intrusion/incident detection, damage control, service continuity, forensic analysis, service/data restoration, and incident reporting. Material covers policy, planning, operations, and technology issues involved in related cyber incident handling plans; i.e., Business Continuity, Disaster Recovery, and Continuity of Operations. Specific incident types addressed include, natural disasters, denial of service, malicious code, malicious misuse of hardware and firmware, unauthorized access, data compromise and inappropriate use, including insider attacks. Emphasis is given to the detection and analysis of infiltration and exfiltration techniques employed during cyber attacks, thus enabling the incident handler to detect low noise attacks, and to deconstruct particularly insidious attacks. Contains a lab component. Prerequisite: CSC 431 (3 units; Fall)

This course provides an advanced course that focuses on key principles of a constructive approach to secure systems. A brief review of operating systems and computer architecture is provided. Major topics include threat characterization and subversion; confinement; fundamental abstractions, principles, and mechanisms, such as reduced complexity, hierarchical relationships, least privilege, hardware protection, resource management and virtualization, software security, secure system composition, mutual suspicion, synchronization, covert and side-channel analysis, secure metadata, secure operational states, usability, and life cycle assurance. Current developments will include advances in security hardware, components, and systems. This course has heavy reliance on software development and implementation. Prerequisite: CSC 431. (3 units; Spring)

Artificial Intelligence (AI) is concerned with the design and analysis of autonomous agents that perceive their environment and make rational decisions. This course introduces the basic definitions and issues in Artificial Intelligence and Machine Learning. Students will create reasoning systems in software and explore their capabilities in dealing with new knowledge. Ethical issues in AI will be presented and examined from a Christian perspective. Prerequisite: EGR 227 (3 units; Spring)

This course covers introductory machine learning topics including supervised and unsupervised learning, linear and logistic regression, support vector machines, neural networks (MLPs, CNNs, RNNs, GANs) and more. Coursework includes instruction and programming assignments in algorithmic implementations and high-level library usage. Students also apply machine learning techniques to a unique research project. Prerequisites: EGR 120 or 121, and one of the following: EGR 305, MAT 353, STA 144, 310, or one additional approved statistic course. (3 units; Fall)

The course commences with an examination of the knowledge discovery process. In particular, the introduction equips students with the strategic thinking skills essential to focus on cutting edge data mining techniques that can be applied in a wide variety of settings, e.g., business, engineering, health care, science, etc. Traditional topics include data mining algorithms and implementation issues, advantages and disadvantages of data mining, and examples of knowledge engineering. Current topics such as ubiquitous, distributed, and spatiotemporal geographic data mining will also be explored. This is a practical hands-on course that culminates in a real-world project implemented via open source tools. Prerequisites: EGR 120 or 121, and one of the following: EGR 305, MAT 353, STA 144, 310, or one additional approved statistics course. (3 units; Fall)

Natural language is ubiquitous, e.g., humans speak and write to communicate, to transfer information, and to document knowledge. Natural Language Processing (NLP) is an integral component in countless information systems requiring advanced manipulation of natural language. In this class, students will be introduced to NLP starting with the concept of understanding words in context and the need for natural language processing in the business environment. The discussion continues with a detailed study of words and is a foundational framework supporting phonetics and speech synthesis. Subsequent topics include concepts of how words are grouped together to form unique grammatical units. The last part of the course, explores solving real-world NLP problems and deals with two key areas: corpus building, feature engineering, and application development. Course material is presented via theory-based lectures, group discussion, and practical labs-a culminating research project will be individually crafted. Prerequisites: EGR 120 or 121, and one of the following: EGR 305, MAT 353, STA 144, 310, or one additional approved statistics course. (3 units; Spring)

This course provides an introduction to the field of Security in computing. Topics include common security standards and policies, cryptography and information security, access controls, attacks and countermeasures, and computer forensics. Prerequisite: EGR 222. (3 units; Spring)