Course Requirements​

Introductory Courses

Foundation Courses 

Advanced Courses

Elective Courses

Students must take 3 graduate level elective courses in the areas of statistical modeling, data mining or database technologies according to the following rules:

Capstone

IT 403

STATISTICS AND DATA ANALYSIS

Introduction to univariate data analysis methods. Descriptive statistics and data visualization methods. Overview of sampling techniques for data collection, and introduction to statistical inference methods for decision making including simple linear regression, estimation procedures using confidence intervals and hypothesis testing. PREREQUISITE(S): None
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 412

TOOLS AND TECHNIQUES FOR COMPUTATIONAL ANALYSIS

Use of mathematical software to explore basic concepts in linear algebra and calculus. Scripting for symbolic and computational processing. Emphasis is on applications in computer science, finance, data mining, and computer vision. PREREQUISITE(S): None
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 401

INTRODUCTION TO PROGRAMMING

An introduction to programming with a focus on problem solving, structured programming, and algorithm design with a gentle introduction to efficiency. Concepts covered include data types, expressions, variables, assignments, conditional and iterative structures, functions, file input/output, exceptions, namespaces, and recursion. PREREQUISITE(S): None
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 451

DATABASE DESIGN

Requirement analysis, conceptual design, logical design and implementation of relational databases. Emphasis will be on E-R modeling and E-R mapping, along with basic normalization and SQL for database implementation. PREREQUISITE(S): None
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 423

DATA ANALYSIS AND REGRESSION

Multiple regression and correlation, residual analysis, analysis of variance, and robustness. These topics will be studied from a data analytic perspective, supported by an investigation of available statistical software. PREREQUISITE(S): IT 403
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 424

ADVANCED DATA ANALYSIS

The course will teach advanced statistical techniques to discover information from large sets of data. The course topics include visualization techniques to summarize and display high dimensional data, dimensional reduction techniques such as principal component analysis and factor analysis, clustering techniques for discovering patterns from large datasets, and classification techniques for decision making. The methods will be implemented using standard computer packages. PREREQUISITE(S): CSC 423 or consent of instructor.
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

IS 567

KNOWLEDGE DISCOVERY TECHNOLOGIES

An introduction to the Knowledge Discovery Technologies covering all stages of a data mining process: domain understanding, data collection and selection, data cleaning and transformation, dimensionality reduction, pattern discovery, evaluation, and knowledge extraction. The course provides a comprehensive overview of data mining techniques used to realize these stages, including traditional statistical analysis and machine learning techniques. Students will analyze large datasets and develop modeling solutions to support decision making in various domains such as healthcare, finance, security, marketing, customer relationship management (CRM), and multimedia. PREREQUISITE(S): IT 403
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 495

SOCIAL NETWORK ANALYSIS

This course is an introduction to the concepts and methods of social network analysis. Students will learn to extract and manage data about network structure and dynamics, and to analyze, model and visualize such data. Students will use software tools to model and visualize network structure and dynamics. Specific network applications to be discussed include online social networks, collaboration networks, and communication networks. PREREQUISITE(S): CSC 423 or CSC 400 or SOC 412
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

ECT 584

WEB DATA MINING FOR BUSINESS INTELLIGENCE

An in-depth study of the knowledge discovery process and its applications in Web mining, Web analytics and business intelligence. The course provides coverage of various aspects of data collection and preprocessing, as well as basic data mining techniques for segmentation, classification, predictive modeling, association analysis, and sequential pattern discovery. The primary focus of the course is the application of these techniques to Web analytics, user behavior modeling, e-metrics for business intelligence, Web personalization and recommender systems. Also addressed are privacy and ethical issues related to Web data mining. Students can choose from three types of final course projects: implementation projects, research papers, or data analysis projects. Throughout the course, the students will learn and use a variety of data mining tools to analyze sample data sets as part of class assignments. PREREQUISITE(S): IT 403 AND (CSC 451 or CSC 453)
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

A&S 491

ADMINISTRATIVE THEORY AND BEHAVIOR

This course concerns theoretical concepts and empirical research relating to administrative behavior in organizations with special reference to educational organizations. Concepts are examined within the typical decisional framework of supervisors, chief school business officers, principles, and superintendents, and similar positions in the helping professions. Assignments are individualized.
Prerequisites:
Status as an Advanced Masters Education student is a prerequisite for this class.

CSC 575

INTELLIGENT INFORMATION RETRIEVAL

Examination of the design, implementation, and evaluation of information retrieval systems. The focus is on the underlying retrieval models, algorithms, and system implementations. Also examined is how an effective information search and retrieval is interrelated with the organization and description of information to be retrieved. Topics include: automatic indexing; thesaurus generation; Boolean, vector-space, and probabilistic models; clustering and classification; information filtering; distributed IR on the WWW; intelligent information agents; IR system evaluation; information visualization; and natural language processing in IR. Throughout the course, current literature from the viewpoints of both research and practical retrieval technologies both on and off the World Wide Web will be examined. PREREQUISITE(S): CSC 403
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

MKT 555

DECISIONS IN MARKETING MANAGEMENT

Students are provided with an overview of the marketing process for consumer-oriented firms. Focus is placed on decision-making that aligns a firm's market offerings with the wants and needs of targeted segments of customers within a continuously changing environment. Written cases/projects are part of the course assignment.

MKT 530

CUSTOMER RELATIONSHIP MANAGEMENT

Students are introduced to a new strategy methodology, CRM, which is currently being adopted by many organizations in efforts to enhance their competitive advantage. Focus is placed on understanding how an enhanced customer relationship environment can differentiate an organization in a highly competitive marketplace. Both the business and consumer markets are examined in multiple vertical markets. New technology demonstrations and their impact will be discussed. Guest speakers provide current best-practice methods. Topics included: Case analysis and projects make up the course assignments.
Prerequisites:
MKT 555 is a prerequisite for this class.

MKT 534

ANALYTICAL TOOLS FOR MARKETERS

This course seeks to provide an in-depth understanding of both qualitative and quantitative analytical tools that are of critical importance to marketers. These tools will help marketers avoid head-to-head competition, understand customer perceptions, understand customer preferences, develope accurate sales forecasts, and financially value marketing strategies. The course is designed to be "hands-on" in that students will develop understanding mainly through conducting application projects and presenting results. The course is also designed to be immediately applicable to marketers' current and future jobs.
Prerequisites:
MKT 555 is a prerequisite for this class.

MKT 529

PRECISION MARKETING

The ever increasing amount of data about consumers and transactions allows marketers to better understand who their customers are and what they are buying. This course explores a wide variety of data sources and how they are used in marketing, with a special emphasis on segmentation, targeting and positioning.Offered winter quarter.
Prerequisites:
MKT 555 is a prerequisite for this class.

MKT 595

INTERNET AND INTERACTIVE MARKETING

Explores the emerging business models, rules, tactics, and strategies associated with this medium. Integration with other channels and marketing operations is stressed. Classes are discussion-based, drawing on current applied readings and cases from a variety of industries in both the business-to-business and business-consumer markets.
Prerequisites:
MKT 555 is a prerequisite for this class.

MKT 578

SALES STRATEGY & TECHNOLOGY

Students taking this course will be provided with a comprehensive understanding of sales strategy and an appreciation of sales technology used today to optimally organize and deploy sales resources. At the heart of this course is an introduction to the principles of customer relationship marketing and customer acquisition programming. Students will learn via lecture, text, guest lectures, exposure to the latest technological tools and current case study. This course will benefit participants by providing a true perspective as to what role sales plays today and will play in the future of customer-centric organizations.
Prerequisites:
MKT 555 is a prerequisite for this class.

CSC 425

TIME SERIES ANALYSIS AND FORECASTING

The course introduces students to statistical models for time series analysis and forecasting. The course topics include: autocorrelated data analysis, Box-Jenkins models (autoregressive, moving average, and autoregressive moving average models), analysis of seasonality, volatility models (GARCH-type, GARCH-M type, etc.), forecasting evaluation and diagnostics checking. The course will emphasize applications to financial data, volatility modeling and risk management. Real examples will be used throughout the course. PREREQUISITE(S): CSC 423 or MAT 456 or consent of instructor
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 433

SCRIPTING FOR DATA ANALYSIS

Data access and transformation with modern statistical software such as SAS and R. Report writing, data graphing and visualization, writing macros and functions to automate tasks and statistical analyses. PREREQUISITE(S): IT 403 and (CSC 401 or IT 411)
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 478

PROGRAMMING DATA MINING APPLICATIONS

The course will focus on the implementations of various data mining and machine learning techniques using a high-level programming language. Students will develop hands on experience developing both supervised and unsupervised machine learning algorithms and will learn how to employ these techniques in the context of popular applications including automatic personalization, recommender systems, searching and ranking, text mining, group and community discovery, and social media analytics. PREREQUISITE(S): IT 403 and CSC 401
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 529

ADVANCED DATA MINING

The course is for students with prior background in data mining or machine learning techniques, and cover more advanced modeling techniques, including ensemble learning, extended linear models such as support vector machines, probabilistic graphical models, mixture and latent variable models, matrix factorization and link analysis. Application of the models will be presented in popular domains such as Web and social media analytics, text mining, crime analysis, community discovery, and health informatics. PREREQUISITE(S): CSC 424 and (IS 567 or ECT 584 or CSC 578)
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 521

MONTE CARLO ALGORITHMS

A course about the use of random numbers for numerical computation with particular emphasis on implementation issues and applications in science and finance. Covered topics include: pseudo random number generators, the inversion method, the accept-reject method, discrete event simulations, multi-dimensional integration, the Metropolis and the Bootstrap algorithms. PREREQUISITE(S): (CSC 402 or CSC 404) and CSC 423 or consent of instructor
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 481

INTRODUCTION TO IMAGE PROCESSING

The course is a prerequisite for more advanced Visual Computing (VC) courses and the students will be challenged to implement VC algorithms for real world applications. The topics covered in the course include: components of an image processing system and its applications, elements of visual perception, sampling and quantization, image enhancement by histogram equalization, color spaces and transformations, introduction to segmentation (Edge detection), and morphological image processing. PREREQUISITE(S): Calculus or Linear Algebra.
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 482

APPLIED IMAGE ANALYSIS

Fundamentals of computational image analysis will be explored in terms of its two most important components, image information extraction and modeling of image patterns. These components will be studied in the context of image representation, segmentation, classification, retrieval and recognition. The course will be useful for students interested in image analysis related to areas such as image databases, multimedia management, animation, GIS, computer graphics, medical imaging, remote sensing and robotics. Specific topics include, but are not limited to segmentation, multi-scale representation, shape analysis, texture analysis, Fourier analysis, wavelets, Gabor and fractal analysis, template matching, and object recognition. PREREQUISITE(S) CSC 481
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

GPH 465

SURVEY OF VISUALIZATION APPLICATIONS

An in-depth introduction to a wide range of visualization techniques focusing on medical and scientific and engineering applications. Introduction to programming using a visualization package, use of color for feature extraction and enhancement, false color mapping techniques, reconstruction techniques, isosurface generation, stream lines and ribbons, spatial set operations, volumetric techniques and projections of higher-dimensional datasets. PREREQUISITE(S): GPH 425 or IT 403
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

GPH 565

DESIGNING FOR VISUALIZATION

Sources of graphical integrity and sophistication. Data-Ink maximization. Data density. The use of color to enhance features in data sets and the communication of information . Effective use of space and time. Use of 3D techniques to display multi-dimensional data. The use of isosurfaces and volumetric techniques to display features of data sets. Students will use a programmable system to produce their visualizations and will learn how to use procedural techniques to express graphical intent. (Only one of GPH 570 and GPH 565 may be taken for credit) Prerequisite(s): GPH 448 and HCI 470
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 453

DATABASE TECHNOLOGIES

A core graduate course in database design and implementation. Topics include database implementation and queries in SQL, logical design or relational databases, storage and indexes, database programming, and emerging database models. PREREQUISITE(S): CSC 403
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 452

DATABASE PROGRAMMING

Programming in large-scale relational database environment using host languages. Design and implementation of on-line applications. Topics covered in this course include: database programming using open architectures, embedded query languages, dynamic query language, procedural extension of query languages, stored procedures, transaction management, and introduction to extensible markup data definition and retrieval languages. PREREQUISITE(S): (CSC 453 or CSC 451) and CSC 401
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 543

SPATIAL DATABASES & GEOGRAPHIC INFORMATION SYSTEMS

This course considers how spatial databases work within a GIS, how data is structured, stored, indexed, retrieved, and displayed. Other topics may include fuzzy spatial databases, temporal spatial databases, and multiple criteria spatial decision making. The class will consist of hands-on work with commercial products, as well as investigating the state of-the art research in the field. Prerequisites: CSC 453.
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

GEO 441

GEOGRAPHIC INFORMATION SYSTEMS (GIS) FOR COMMUNITY DEVELOPMENT

This course will focus on applications of Geographic Information Systems (GIS) to community studies and community development. As an amalgam of information technologies (e.g. database management, Web 2.0) and earth measurement technologies (e.g. global positioning systems, remote sensing), GIS is rapidly entering the realm of community development. The course will explain how GIS works; enable students to learn techniques including mapping, spatial analysis, and data management; and provide students with the opportunity to apply GIS to community development.

CSC 598

TOPICS IN DATA ANALYSIS

Specific topics will be selected by the instructor and may vary with each quarter. Can be repeated for credit. Variable credit. PREREQUISITE(S): For specific prerequisites, see syllabus or consult course instructor.
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

IS 549

DATA WAREHOUSING AND DATA MINING

Introduction to data warehousing and the foundations of understanding the issues involved in building a successful data warehouse. Data warehouse development methodology and issues surrounding the planning of the data warehouse. Data quality and metadata in the data warehouse. Analysis, transformation and loading of data into a data warehouse. Development of the data architecture and physical design. Implementation and administration of the data warehouse. Introduction to data mining. (PREREQUISTE(S):CSC 451 or CSC 453
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

IS 574

BUSINESS INTELLIGENCE

Introduction to the concepts of business intelligence (BI) as components and functionality of information systems. How business problems can be solved effectively by using operational data to create data warehouses, and then applying data mining tools and analytics to gain new insights into organizational operations. Detailed discussion of the analysis, design and implementation of systems for BI, including: data management systems, decision support systems, group support systems, knowledge engineering, expert systems, and Web 2.0 tools. Case studies of application software, web tools, success and limitation as well as technical and social issues. (PREREQUISITE(S): (SE 430 or IS 435 or PM 430 or MIS 674) and CS C451
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

IS 578

INFORMATION TECHNOLOGY CONSULTING

This course is for the IT professional. The emphasis is on examining the models, techniques, and skill development for providing effective IT consulting services. The course examines the structure of IT consulting markets; leading IT consulting practices; models and approaches for providing internal IT consulting services; sourcing strategies, evaluation of RFPs and response process contract formulation, client relations and project management; knowledge management and collaboration and IT strategies. PREREQUISITE(S): Completion of foundation or core phase.
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

CSC 695

MASTER'S INDEPENDENT STUDY (1 - 4 CREDITS)

Students interested in a more in-depth study of a particular area will register for this course and work with a faculty member (not necessarily their academic advisor) on a research project. The work involved may include system development, empirical studies, or theoretical work. 4 credit-hours of CSC695 replace one 500-level CS elective course in the MS in CS program and can be taken for up to 8 credit-hours. PREREQUISITE(S): Consent of research advisor. Independent study form required. Students must successfully complete the Core Knowledge Phase courses prior to their first enrollment in CSC 695

CSC 697

GRADUATE INTERNSHIP

In cooperation with local employers, the graduate program offers students the opportunity to integrate their academic experience with on-the-job training in computer related work areas. This course is offered for one credit and admission to the program requires consent of a Student Services Advisor. International students may complete curricular practical training through this class.
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.

MKT 798

SPECIAL TOPICS

Content and format of this course is variable. An in-depth study of current issues in marketing.

CSC 455

DATABASE PROCESSING FOR LARGE-SCALE ANALYTICS

The course covers core concepts of database systems with focus on applications in large-scale analytics. Topics include relational databases, scheme normalization, SQL queries for data integration and data cleaning, database programming for ETL, and nontraditional database systems for unstructured data. PREREQUISITE(S): CSC 401