Course Requirements
Introductory Courses
Introductory courses may be waived for any of the following conditions:
- The student has the appropriate course work to satisfy an Introductory Course.
- The student has appropriate and verified professional experience to satisfy an Introductory Course.
- The student passes a Graduate Assessment Examination (GAE) in the Introductory Course area.
CDM Foundation Courses
Kellstadt Foundation Courses
Advanced Courses
Major Elective Courses
Students must take 1 500-level course at CDM, Kellstadt, or the Department of Math.
Degree Requirements
Students in this degree program must meet the following requirements:
- Complete a minimum of 52 graduate credit hours in addition to any required introductory courses of the designated degree program.
- Complete all graduate courses and requirements listed in the designated degree program.
- Earn a grade of B- or better in each introductory course of the designated degree program.
- Earn a grade of C- or better in all courses beyond the introductory courses of the designated degree program.
- Maintain a cumulative GPA of 2.5 or higher.
- Students pursuing a second master's degree must complete a minimum of *52 graduate credit hours beyond their first designated degree program in addition to any required introductory courses in their second designated degree program.
*53 graduate credit hours required for MS Information Systems.
Students with a GPA of 3.9 or higher will graduate with distinction.
For DePaul's policy on repeat graduate courses and a complete list of academic policies see the DePaul Graduate Handbook.
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): IT223.
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering 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): (CSC423 or MAT456) or consent of instructor
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.
CSC 431
SCIENTIFIC COMPUTING
This course presents fundamental numerical algorithms for solving problems in scientific computing and computational finance. Areas covered include: error analysis, computer arithmetic, linear algebra, optimization problems, numerical integration (solvers), ordinary differential equations (ODE). The emphasis of the course is on the design of the algorithms, and their analysis. Algorithms will be implemented using mathematical software. PREREQUISITE(S): CSC 212 or CSC 262 or CSC 242 or CSC 300, and 2 course calculus sequence or instructor's permission.
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.
CSC 485
NUMERICAL ANALYSIS
Use of a digital computer for numerical computation. Error analysis, Gaussian elimination and Gauss-Seidel method, solution of nonlinear equations, function evaluation, approximation of integrals and derivatives, Monte Carlo methods. PREREQUISITE(S): MAT 220 and a programming course.
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. Prerequisites: CSC 262, CSC 212, CSC 301 or CSC 309, or CSC 224 and CSC 423 or instructor's permission
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.
ACC 500
FINANCIAL ACCOUNTING
This introduction to financial accounting provides both a theoretical foundation and an opportunity to apply accounting logic in increasingly complex situations. The accounting model and information processing cycle are developed. The content of the income statement, balance sheet, and statement of cash flows are studied in detail and analyzed.
Prerequisites:
MS in Taxation students are restricted from registering for this class.
ECO 555
ECONOMICS FOR DECISION-MAKING
This course provides students with an opportunity to apply microeconomic principles to managerial decision-making. These principles include those underlying the theories of consumer choice, production and cost as they relate to decisions made by firms and households. Specific topics include consumer demand analysis and estimation; elasticity; production theory; cost structure and estimation; profit maximization; and the effect of market structure on pricing, output and profit.
Prerequisites:
GSB 420 is a prerequisite for this class.
FIN 555
FINANCIAL MANAGEMENT
A study of the major decision areas faced by the corporate financial manager and their relationship to the goals of the firm's owners. Specific topics include capital budgeting, capital structure and the cost of capital, dividend policy, and current asset management.
Prerequisites:
ACC 500 and (ECO 555 or equivalents) and GSB 420 are a prerequisite for this class.
FIN 523
INVESTMENT ANALYSIS
This course provides an overview of the investment environment for the institutional money manager. The market mechanism, market equilibrium, the relationship between risk and return and the valuation of various investment instruments are investigated.
Prerequisites:
FIN 555 and GSB 420 are prerequisites for this class.
FIN 525
PORTFOLIO MANAGEMENT
This course analyzes contemporary theories and techniques of security selection and management available to the institution portfolio manager. Significant literature which emphasizes the role of the modern portfolio manager in achieving diversification and client investment goals is reviewed and evaluated.
Prerequisites:
FIN 523 is a prerequisite for this class.
FIN 562
RISK MANAGEMENT
This course is designed as an introduction to derivative instruments; their characteristics, their pricing, the market's infrastructure, trading mechanics, and applications. The course introduces the binomial pricing model, the Black & Scholes continuous time pricing model, the associated properties i.e. "the Greeks." and forward pricing. The course examines the characteristics and market infrastructure for each of the four derivative instruments: foreard, futures, options, and swaps. Then trading strategies and hedging applications for each of these instruments are discussed. The course concludes with an introduction to Value at Risk.
Prerequisites:
FIN 555 and GSB 420 are prerequisites for this class.
FIN 662
DERIVATIVES VALUATION
This course is designed to be an advanced course that focuses on the pricing models for the four derivative instruments: forwards, futures, options and swaps. Fixed income modeling as it is related to swaps and caps also will be considered. The first part of the course is devoted to an in depth examination of the various pricing models: discrete, continuous time, as well as Monte Carlo simulation. Each model's properties are derived and discussed in detail. These models are then applied to a range of realistic pricing situations which include swaps, exotic options, credit derivatives and complex Value at Risk problems.
Prerequisites:
FIN 555 is a prerequisite 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
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.
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.
CSC 559
SOFTWARE ENGINEERING FOR FINANCIAL MARKETS
This course focuses on software engineering issues in creating a financial engine that drives automation and execution in a financial market. The course will cover different types of financial engines from back-office to front-office, exchange matching engines, data gathering engines, trading engines and straight through processing. The emphasis will be on the engines themselves rather than the financial models beneath them. Students will be required to work individually and/or in teams and create a financial engine. This is a project course and it will put students in the role of a domain architect who will need the skills required to communicate with financial traders and software engineers at the same time. PREREQUISITE(S): (CSC309 or CSC262) and (CSC431 or CSC521 or CSC425)
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 404
ACCELERATED C++
This introductory graduate course covers the essentials of C++ programming. Topics include encapsulation, inheritance, polymorphism, dynamic memory allocation, casting, pointer arithmetic, operator overloading, templates, and teh Standard Template Libraries. PREREQUISITE(S): None
Prerequisites:
CDM graduate students in the Preqrequisite Phase are restricted from registering for this class.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.