Info Sys & Decision Sciences
DS 70. Quantitative Analysis Support
Prerequisite: Mathematics placement category III or IV. This is a one-unit, credit/no-credit course, employing a stretch model, specifically focused on preparing CSU Math-Ready Category III and IV students for DS 71. (DS 71 being a GE course in Quantitative Reasoning that meets the campus Area B4 graduation requirement.) (Formerly DS 189T)
Units: 1
Course Typically Offered: Fall, Spring
DS 71. Quantitative Analysis
Prerequisite: Mathematics placement category I or II. Students in Mathematics placement category III and IV must pass DS 70 with a CR or Math 3 with a C or better. Quantitative formulation and solution of problems in various disciplines, including mathematics of finance, linear programming, probability, and differential calculus. G.E. Foundation B4.
Units: 3
Course Typically Offered: Fall, Spring
GE Area: B4
DS 71L. Quantitative Analysis Lab
Prerequisite: concurrent enrollment in DS 71. DS 71L is not required for DS 71. Extends instruction in DS 71, providing three hours of additional support per week. One-on-one tutoring. Small group and technology-enhanced instruction relating to DS 71 curriculum. CR/NC grading only. (Does not apply to major.)
Units: 1
Course Typically Offered: Fall, Spring
DS 72. Foundations of Data Science
Prerequisites: College Math readiness Category I and II. For students at Category III and IV, check specific majors and programs for requirements. Combines perspectives of computational and inferential thinking. Teaches critical concepts and skills of programming and statistical inference. It further delves into social issues surrounding data analysis such as privacy. It utilizes real-world datasets from a variety of disciplines such as business, economic, geographical and social networks. G.E. Foundation B4.
Units: 3
Course Typically Offered: Fall, Spring
GE Area: B4
DS 73. Statistical Analysis I
Prerequisites: DS 71 or equivalent; ECON 40, ECON 50 recommended. Introduction to descriptive statistical tools as applied to management decision making. Central tendency and dispersion measures; index numbers (CPI deflators); time series analysis (trends, seasonal variations)probability theory; probability and sampling distributions (normal, exponential, binomial, Poisson); central limit theorem.
Units: 3
Course Typically Offered: Fall, Spring
DS 73L. Statistical Analysis I Lab
Prerequisite: concurrent enrollment in DS 73. DS 73L is not required for DS 73. Extends instruction in DS 73, providing three hours of additional support per week. One-on-one tutoring. Small group and technology-enhanced instruction relating to DS 73 curriculum. (Does not apply to major.) CR/NC grading only.
Units: 1
Course Typically Offered: Fall, Spring
DS 123. Statistical Analysis II
Prerequisites: DS 71, DS 73, IS 52, IS 52L. Statistical inference as applied to managerial problems and decision making. Emphasizes the inferential process; interval estimation, hypothesis testing, one- and two-way analysis of variance, regression, and correlation and related inferential analysis, nonparametric methods, Bayesian decision theory.
Units: 3
DS 123L. Statistical Analysis II Lab
Prerequisite: Concurrent enrollment in DS 123. DS 123L is not required for DS 123. Extends instruction in DS 123, providing three hours of additional instructional support per week. One-on-one tutoring, small group and technology enhanced instruction relating to DS 123 curriculum. CR/NC grading only. (Does not apply to major).
Units: 1
Course Typically Offered: Fall, Spring
DS 133. Business Intelligence with Advanced Spreadsheet
Prerequisite: DS 71, DS 73, IS 52, IS 52L and DS123 (DS 123 can be co-requisite) with the grade of "C" or better. Advanced features of spreadsheets (i.e. Excel) for data analysis. It introduces tools and applications of visualization while building pragmatic solutions to business problems. It follows a problem-solution format to explore data analysis and cover best-practices for delivering solutions. The course introduces machine learning concepts and applications with Artificial Intelligence. (2 lecture, 2 lab hours)
Units: 3
Course Typically Offered: Spring
DS 135. Data Analytics
Prerequisite: DS 123 or consent of the instructor. Analysis of large datasets to discover relationships and improve prediction and decision making. Techniques include data visualization, online analytical processing, multiple regression, logistic regression, recursive portioning, neural networks, and cluster analysis. Management applications and software tools. (2hr lec, 2hr lab) (Formerly DS 189T)
Units: 3
DS 137. Machine Learning
Prerequisite: DS 123. Machine learning involves studying computer algorithms that automatically improve their performance through experience. Covers core concepts, algorithms, & applications of machine learning in business scenarios. Supervised learning topics such as classification (Naive Bayes, Logistic regression, neural networks, k-NN, decision trees, boosting) and regression (linear, nonlinear, kernel, nonparametric), as well as unsupervised learning (clustering, PCA, dimensionality reduction). Python will be the language used in this course. (2 lecture and 2 lab hours) (Formerly DS 189T)
Units: 3
Course Typically Offered: Spring
DS 140. Prescriptive Analytics
Prerequisite: DS 123 or equivalent course or consent of the instructor. This course introduces the prescriptive analytics methodologies, optimization, and simulation. A wide range of topics are covered including linear programming, integer programming, mixed integer linear programming, nonlinear programming, stochastic programming, and simulation models. Emphasize how to develop such models effectively using software tools on real business problems.
Units: 3
Course Typically Offered: Fall, Spring
DS 189T. Topics in Decision Sciences
Prerequisites: 12 units in decision sciences. Theory or application of statistics or operations research applied to current developments.
Units: 1-3, Repeatable up to 6 units
DS 190. Independent Study
See Academic Placement -- Independent Study. Approved for RP grading.
Units: 1-3, Repeatable up to 6 units
Course Typically Offered: Fall, Spring
DS 195I. Internship
Prerequisite: permission of internship coordinator. Requires 150 hours of work at a prequalified, academically-related work station (business, government, or nonprofit agency.) Reflective journal, final report, and work station evaluation. CR/NC grading only. As a course substitution, prior department approval required. Only one internship may count towards option requirements.
Units: 3, Repeatable up to 6 units
Course Typically Offered: Fall, Spring
IS 51. Programming Fundamentals
Prerequisite: IS 52 and IS 52L or equivalent. Structured program design using Microsoft Visual Studio. Concepts of object-oriented and event-driving programming, user interface design, algorithm development, testing and debugging, and documentation using business examples. (2 lecture, 2 lab hours)
Units: 3
Course Typically Offered: Fall, Spring
IS 52. Computer Concepts
Introduction to computer hardware and software systems, impact of computers on society, ethical issues, application of computer technology in many career fields. No credit if taken after IS 50 (Formerly IS 50)
Units: 2
Course Typically Offered: Fall, Spring
IS 52L. Computer Concepts Lab
Hands-on study of office productivity software to include elements of word processing, electronic spreadsheets, database, and presentation software. Modules may differ by major. Some sections utilize self-paced computer-based training. No credit if taken after IS 50. (2 lab hours) CR/NC grading only. (Formerly IS 50)
Units: 1
Course Typically Offered: Fall, Spring
IS 106. Client-Side Software Architecture
Prerequisites: IS 51, IS 158 (may be taken concurrently). Theory and practice of software design and development and source control management system. Concepts of UI/UX design optimization and the basics of web-based framework client-side programming. Introduction to Internet architecture concepts, protocols, and application deployment. (2 lecture, 2 lab hours)
Units: 3
IS 130. Information Systems
Prerequisites: IS 52 and IS 52L or equivalent. Use of information systems in business activities throughout global organizations. Integration of people, software, hardware, data, and communication technologies to create competitive advantage. Information technology as enabler of process improvement in quality, flexibility, speed and as facilitator of decision-making. Application software prevalent or emerging in organizations. Hands-on practice with spreadsheet, database, analytics, and other leading software applications.
Units: 3
Course Typically Offered: Fall, Spring
IS 140. Geographic Information Systems (GIS) for Business
Prerequisites: solid computer skills. Application of geographic information systems to solution of business problems. Study of GIS concepts, software, management, ethical issues, and cases using local data and problems. (2 lecture, 2 lab hours) (Formerly IS 156T)
Units: 3
Course Typically Offered: Fall
IS 141. Cyber-Security
Prerequisites: IS 130 or consent of instructor. Comprehensive overview of the essential concepts students must know as they pursue careers in information systems security. Students will learn critical principles that enable them to plan, develop, and perform security tasks. Topics include hardware, software, processes, communications, applications, and policies and procedures with respect to organized IT security and Risk Management. (Formerly IS 189T.)
Units: 3
IS 153. Enterprise Resource Planning Systems
Introduction to the concept of Enterprise Resource Planning (ERP) as integrating process data across several functions of an organization. Fundamental techniques for the operation and configuration of ERP systems. Successful selection and implementation on ERP Systems. Hands-on practice using a leading ERP system. (2 lecture, 2 lab hours) (Formerly IS 156T)
Units: 3
Course Typically Offered: Fall, Spring
IS 156T. Topics in Emerging Information Technologies
Prerequisites: IS 52, 52L. Overview of the most recent tools and techniques in information technology, and their utilization in the business environment with specific content of the course updated and refocused every year. (2 lecture, 2 lab hours)
Units: 3, Repeatable up to 6 units
IS 156T. Introduction to Cloud Architecting
Students will learn and understand both the business, economy, cost, and technical drivers of the IT industry. Students must know the why before the how: Why does a business exist, what is it trying to do (use case). By the end of this course students will be not only be able to architect, but architect well. The course will follow industry best practices of developing cost effective, scalable, and highly available systems. This course assumes no prior cloud computing knowledge nor any knowledge of multi-layered IT infrastructure (networking, DB, web services, compute, or security). (2 lecture, 2 lab hours) This topic may not be repeated for credit. (Offered Fall 2023)
Units: 3
IS 158. Database Design and SQL
Prerequisites: IS 51 or instructor consent. Concepts in data and database design. Identifying information requirement; modeling techniques; relational data models; normalization; using industrial-strength database management system. Data retrieval with standard query language, SQL (2 lecture, 2 lab hours)
Units: 3
Course Typically Offered: Fall, Spring
IS 160. Artificial Intelligence in Business
Prerequisites: IS 170. Building on top of the machine learning applications, this course presents the concepts and algorithms of deep learning (DL) and reinforcement learning (RL). Student will: 1) learn the mathematical concepts of DL and RL, 2) understand how to setup DL & RL models using leading coding platform, 3) exercise critical thinking for the data preparation ? feature engineering and 4) explore DL & RL business applications. The essential topics such as gradient descent and Markov decision process are emphasized. (Formerly IS 189T)
Units: 3
Course Typically Offered: Fall
IS 166. Information Systems, Analysis and Design
Prerequisites: IS 158 with a C or higher grade, ACCT 4A, ACCT 4B, and upper-division standing. Systems approach to problem solving; systems development life cycle; systems analysis; use of system modeling tools; logical systems design, including user interfaces, database, structure, and controls; implementation and testing. (2 lecture, 2 lab hours)
Units: 3
IS 170. Machine Learning Applications
Prerequisites: IS 51 or instructor consent and IS 130. Machine Learning, a sub-domain of Artificial Intelligence, encompasses supervised and unsupervised (data mining) algorithms used to process business data. Introduction to each topic/algorithm?s definition, background, concept, coding, and evaluation of business applications and implications. Hands-on coding and executing algorithms. A set of latest machine learning tools and software applications are used. (2 lecture, 2 lab hours) (Formerly IS 156T)
Units: 3
Course Typically Offered: Spring
IS 181. Computer Networks Management
Prerequisites: IS 52, IS 52L. Theory and practice of computer network design, installation, and management focusing on the role of the information communications system in a distributed business computing environment. Concepts include network operating systems, protocols, topologies, security, supporting services, applications, and disaster recovery. (2 lecture, 2 lab hours)
Units: 3
Course Typically Offered: Fall, Spring
IS 182. Advanced Network Design and Management
Prerequisites: IS 181. Design and management of advanced business telecommunications network components and services. Conceptual foundation and direct hands-on experience in designing, installing, and managing the relevant equipment, software, and services. (2 lecture, 2 lab hours) (Formerly IS 156T)
Units: 3
Course Typically Offered: Fall
IS 183. Web Development and Mobile Design
Prerequisites: IS 51, IS 106, IS 158 (IS 158 and IS106 may be taken concurrently). Theory and practice of advanced software development, authoring, and source control management. Authoring of Dynamic HTML and cascading style sheets; Web-based e-commerce application design (client-side scripting and server-side scripting with a back-end database), and an introduction to native mobile applications development using a hybrid approach (iOS and/or Android). (2 lecture 2 lab hours)
Units: 3
Course Typically Offered: Spring
IS 186. Project Management
(Same as MGT 158.) Fundamental concepts and techniques addressing all phases, process groups, and knowledge areas in the Project Management Body of Knowledge; software tools for planning, scheduling, and control of projects; satisfies education requirements for Project Management Institute PMP and CAPM certifications. (2 lecture, 2 lab hours)
Units: 3
Course Typically Offered: Fall, Spring
IS 187. IS Practicum
Prerequisites: IS 158, IS 166; senior standing. Integration and application of IS skills and knowledge across business functional areas. Students learn to deliver practical and strategic solutions in an integrative organizational environment. Students work in groups as consultants to solve real business problems. Course incorporates ethical considerations into decision-making. Students undergo competitive review and evaluation. (2 lecture, 2 lab hours)
Units: 3
Course Typically Offered: Fall, Spring
IS 189T. Topics in Information Systems
Prerequisite: permission of instructor. Theory or application of information systems or information management as applied to current developments in the field.
Units: 1-3, Repeatable up to 6 units
IS 190. Independent Study
See Academic Placement -- Independent Study. Approved for RP grading.
Units: 1-3, Repeatable up to 6 units
Course Typically Offered: Fall, Spring
IS 195I. Internship
Prerequisite: permission of internship coordinator. Requires 150 hours of work at a pre-qualified, academically related work station (business, government, or nonprofit agency). Reflective journal, final report, and work station evaluation. As a course substitution, prior department approval required. Only one internship may count towards option requirements. CR/NC grading only.
Units: 3, Repeatable up to 6 units
Course Typically Offered: Fall, Spring
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