BS in Math/Computer Science
BS in Math/Computer Science
Exceptional students with an interest in the highly theoretical nexus of math and computer science will find challenging opportunities from the Bachelor of Science in Math and Computer Science Degree.
Mathematics are a key element to the theory and practice of computer science and technology:
- Number theory forms the basis for encryption algorithms for messages sent over the Internet.
- Facts from projective geometry and multivariable calculus underlie the computer algorithms that control computer animation
- Properties of abstract groups are instrumental in correcting transmission errors that occur when information is sent from one computer to another
- Graph theory and combinatorics are used to create algorithms for Internet search engines and analyze Internet routing protocols
This joint major program is intended to appeal to academically talented students. It is designed to prepare them for graduate study in various areas of computer science such as theoretical computer science, graphics, data analysis, artificial intelligence, and computational methods and in areas in applied mathematics such as numerical analysis or discrete mathematics.
The program is also designed to prepare students to compete for the more theoretical complex jobs found in in computer software development.
Students can choose advanced computer science and mathematics classes from different areas including:
- Theory of computation
- Computational mathematics
- Artificial intelligence
- Data analysis
- Graphics
- Computer vision.
It is highly recommended that students concentrate on one or two areas for their advanced classes to achieve depth, but they are not required to do so. Faculty advisor are available to assist students in their selection.
To view Undergraduate Program Requirements for previous years click here.
The BS in Mathematics and Computer Science consists of five parts:
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The DePaul Liberal Studies Program (19 Courses, not including the capstone course)
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Core Courses (14 Courses)
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Advanced Classes (7 Courses)
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Capstone (1 Course)
-
Open Electives (7 Courses)
The courses in the Core build the necessary foundation in discrete and continuous mathematics, problem solving, algorithmic thinking and programming. The Advanced Classes allow the student to explore the different areas of mathematics and computer science in more depth.
B.S. in Math and Computer Science
Core Classes (14 courses)
Mathematical Foundation
| Offered Fall | |
| In class | Online | |
| √ | |
MAT 140 Discrete Mathematics I
| | √ | |
MAT 141 Discrete Mathematics II
| | √ | |
MAT 260 Multivariable Calculus I
| | | |
MAT 262 Linear Algebra
| | | |
In addition, students must complete one of the following three-course sequences:
| Offered Fall | |
| In class | Online | |
| √ | |
MAT 150 Calculus I
| | √ | |
AND
MAT 151 Calculus II
| | √ | |
AND
MAT 152 Calculus III [prereq
| | | |
OR
| Offered Fall | |
| In class | Online | |
| √ | |
MAT 160 Calculus for Mathematics and Science Majors I
| | | |
AND
MAT 161 Calculus for Mathematics and Science Majors II
| | | |
AND
MAT 162 Calculus for Mathematics and Science Majors III [prereq
| | | |
OR
| Offered Fall | |
| In class | Online | |
| √ | |
MAT 170 Calculus I with Scientific Applications
| | | |
AND
MAT 171 Calculus II with Scientific Applications [prereq
| | | |
AND
MAT 172 Calculus III with Differential Equations [prereq
| | | |
Problem Solving, algorithms, and structured programming
| Offered Fall | |
| In class | Online | |
| √ | |
CSC 241 Introduction to Computer Science I
| | | |
CSC 242 Introduction to Computer Science II
| | | |
CSC 321 Design and Analysis of Algorithms
| | √ | √ |
CSC 383 Data Structures and Algorithms in Java
| | | |
OR
CSC 393 Data Structures in C++
| | | |
Object-Oriented Programming
Computer Systems
| Offered Fall | |
| In class | Online | |
| √ | √ |
CSC 373 Computer Systems I
| | √ | √ |
CSC 374 Computer Systems II
| | | |
Advanced Classes (7 courses)
Students can choose advanced computer science and mathematics classes from different areas including theory of computation, computational mathematics, artificial intelligence, data analysis, graphics, and computer vision. It is recommended that students concentrate on one or two areas for their advanced classes to achieve depth, but they are not required to do so. Students are strongly encouraged to discuss course selection with an advisor.
Students choose seven courses from the following area lists. At least three of the courses have to be in computer science (or graphics) and at least three in mathematics. Courses not on this list need to be approved by an advisor. In particular, students may wish to arrange with a professor to take an independent study or a research experience (MAT 399 or CSC 399 or IT 300) in order to explore a subject more deeply than is possible in a scheduled course.
Theory of Computation Area
The courses in the theory area explore the mathematical and logical foundations of computer science.
| Offered Fall | |
| In class | Online | |
| | |
MAT 302 Combinatorics
| | | |
MAT 303 Theory of Numbers [prereq
| | √ | |
MAT 351 Probability and Statistics I
| | √ | |
MAT 310 Abstract Algebra I [prereq
| | | |
MAT 311 Abstract Algebra II
| | | |
MAT 312 Abstract Algebra III
| | √ | |
MAT 335 Real Analysis I [prereq
| | | |
MAT 372 Logic and Set Theory
| | | |
CSC 235 Problem Solving
| | | |
CSC 327 Problem Solving for Contests
| | | |
CSC 333 Cryptology
| | √ | |
CSC 344 Automata Theory and Formal Grammars
| | √ | |
CSC 347 Concepts of Programming Languages
| | | |
CSC 348 Introduction to Compiler Design
| | | |
CSC 387 Operations Research I: Linear Programming
| | | |
OR
MAT 387 Operations Research I:linear Programming
| | | |
CSC 389 Theory of Computation
| | | |
CSC 358 Symbolic Programming
| | | |
Computational Methods Area
The computational methods area investigates quantitative and computational methods in computer science.
| Offered Fall | |
| In class | Online | |
| | |
CSC 331 Scientific Computing
| | | |
CSC 385 Numerical Analysis
| | | |
OR
MAT 385 Numerical Analysis I
| | | |
CSC 386 Advanced Numerical Analysis
| | | |
OR
MAT 386 Numerical Analysis II
| | | |
MAT 330 Methods of Computation and Theoretical Physics I
| | | |
MAT 331 Methods of Computation and Theoretical Physics II
| | | |
MAT 384 Mathematical Modeling
| | | |
Artificial Intelligence Area
For students with an interest in the computational relations between syntax and semantics.
| Offered Fall | |
| In class | Online | |
| | |
CSC 380 Foundations of Artificial Intelligence
| | √ | |
CSC 357 Expert Systems
| | | |
CSC 358 Symbolic Programming
| | | |
Data Analysis Area
For Students who are interested in statistical and computational Analysis of data. Many of the courses in this area require the student to take MAT 351-353.
| Offered Fall | |
| In class | Online | |
| | |
CSC 328 Data Analysis for Experimenters
| | | |
CSC 334 Advanced Data Analysis
| | | |
OR
MAT 354 Multivariate Statistics
| | | |
CSC 332 Simulation and Modeling
| | | |
OR
MAT 359 Simulation Models and the Monte Carlo Method
| | | |
CSC 367 Introduction to Data Mining
| | | |
MAT 261 Multivariable Calculus II
| | √ | |
MAT 351 Probability and Statistics I
| | | |
MAT 352 Probability and Statistics II
| | | |
MAT 353 Probability and Statistics III
| | | |
MAT 355 Stochastic Processes
| | √ | |
MAT 357 Nonparametric Statistics
| | √ | |
MAT 370 Advanced Linear Algebra
| | √ | |
MAT 356 Applied Regression Analysis
| | | |
MAT 358 Applied Time Series and Forecasting
| | | |
Graphics Area
The graphics courses are intended for students who want to study the technical and mathematical foundations of computer graphics and animation.
| Offered Fall | |
| In class | Online | |
| | |
MAT 337 Complex Analysis
| | | |
MAT 261 Multivariable Calculus II
| | √ | |
MAT 370 Advanced Linear Algebra
| | | |
CSC 385 Numerical Analysis
| | | |
OR
MAT 385 Numerical Analysis I
| | √ | |
GPH 211 Perceptual Principles for Digital Environments I
| | √ | |
GPH 212 Perceptual Principles for Digital Environments II
| | √ | |
GPH 325 Survey of Computer Graphics
| | | |
GPH 329 Computer Graphics Development II
| | | |
GPH 336 Smooth Surface Modeling for Graphics and Animation
| | | |
GPH 372 Principles of Computer Animation
| | | |
Computer Vision Area
Computer vision studies the mathematical and algorithmic underpinnings of image analysis and image processing.
| Offered Fall | |
| In class | Online | |
| | |
MAT 261 Multivariable Calculus II
| | √ | |
MAT 335 Real Analysis I [prereq
| | | |
MAT 381 Fourier Analysis and Special Functions
| | √ | |
MAT 370 Advanced Linear Algebra
| | | |
MAT 384 Mathematical Modeling
| | | |
CSC 381 Introduction to Digital Image Processing
| | | |
CSC 382 Applied Image Analysis
| | | |
CSC 384 Introduction to Computer Vision
| | | |
Capstone Courses (1 course)
Students can choose from several capstone courses, depending on their interest and coursework:
| Offered Fall | |
| In class | Online | |
| | |
CSC 378 Software Projects for Community Clients
| | √ | |
CSC 394 Software Projects
| | | |
GPH 395 Computer Graphics Senior Project
| | | |
MAT 398 Senior Capstone Seminar [sryr]
| | | |
Students need to make sure that they cover all prerequisites of their respective capstone (possibly using open electives).
Open Electives (7 courses)
Students choose seven (7) open electives. Open Electives may be taken from any department or program. These are the only courses that may be taken under the pass/fail option (see the undergraduate Bulletin for details). If you wish to pursue a minor, most minor field courses will be credited as open electives.
Grades:
Grades for all courses in the students major (i.e. non-Liberal Studies and non-Open Elective) must be 'C' or better. Grades of 'C-' may be accepted provided the overall grade point average in the major is 2.0 or better.
All courses in degree
- CSC 224 Java for Programmers
- CSC 235 Problem Solving
- CSC 241 Introduction to Computer Science I
- CSC 242 Introduction to Computer Science II
- CSC 309 Object-Oriented Programming in C++
- CSC 321 Design and Analysis of Algorithms
- CSC 327 Problem Solving for Contests
- CSC 328 Data Analysis for Experimenters
- CSC 331 Scientific Computing
- CSC 332 Simulation and Modeling
- CSC 333 Cryptology
- CSC 334 Advanced Data Analysis
- CSC 344 Automata Theory and Formal Grammars
- CSC 347 Concepts of Programming Languages
- CSC 348 Introduction to Compiler Design
- CSC 357 Expert Systems
- CSC 358 Symbolic Programming
- CSC 367 Introduction to Data Mining
- CSC 373 Computer Systems I
- CSC 374 Computer Systems II
- CSC 378 Software Projects for Community Clients
- CSC 380 Foundations of Artificial Intelligence
- CSC 381 Introduction to Digital Image Processing
- CSC 382 Applied Image Analysis
- CSC 383 Data Structures and Algorithms in Java
- CSC 384 Introduction to Computer Vision
- CSC 385 Numerical Analysis
- CSC 386 Advanced Numerical Analysis
- CSC 387 Operations Research I: Linear Programming
- CSC 389 Theory of Computation
- CSC 393 Data Structures in C++
- CSC 394 Software Projects
- GPH 211 Perceptual Principles for Digital Environments I
- GPH 212 Perceptual Principles for Digital Environments II
- GPH 325 Survey of Computer Graphics
- GPH 329 Computer Graphics Development II
- GPH 336 Smooth Surface Modeling for Graphics and Animation
- GPH 372 Principles of Computer Animation
- GPH 395 Computer Graphics Senior Project
- MAT 140 Discrete Mathematics I
- MAT 141 Discrete Mathematics II
- MAT 150 Calculus I
- MAT 151 Calculus II
- MAT 152 Calculus III [prereq
- MAT 160 Calculus for Mathematics and Science Majors I
- MAT 161 Calculus for Mathematics and Science Majors II
- MAT 162 Calculus for Mathematics and Science Majors III [prereq
- MAT 170 Calculus I with Scientific Applications
- MAT 171 Calculus II with Scientific Applications [prereq
- MAT 172 Calculus III with Differential Equations [prereq
- MAT 260 Multivariable Calculus I
- MAT 261 Multivariable Calculus II
- MAT 262 Linear Algebra
- MAT 302 Combinatorics
- MAT 303 Theory of Numbers [prereq
- MAT 310 Abstract Algebra I [prereq
- MAT 311 Abstract Algebra II
- MAT 312 Abstract Algebra III
- MAT 330 Methods of Computation and Theoretical Physics I
- MAT 331 Methods of Computation and Theoretical Physics II
- MAT 335 Real Analysis I [prereq
- MAT 337 Complex Analysis
- MAT 351 Probability and Statistics I
- MAT 352 Probability and Statistics II
- MAT 353 Probability and Statistics III
- MAT 354 Multivariate Statistics
- MAT 355 Stochastic Processes
- MAT 356 Applied Regression Analysis
- MAT 357 Nonparametric Statistics
- MAT 358 Applied Time Series and Forecasting
- MAT 359 Simulation Models and the Monte Carlo Method
- MAT 370 Advanced Linear Algebra
- MAT 372 Logic and Set Theory
- MAT 381 Fourier Analysis and Special Functions
- MAT 384 Mathematical Modeling
- MAT 385 Numerical Analysis I
- MAT 386 Numerical Analysis II
- MAT 387 Operations Research I:linear Programming
- MAT 398 Senior Capstone Seminar [sryr]
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Because mathematical theorems inform computer science in a number of ways, Math/Computer Science degree graduates are doubly prepared for career opportunities in a number of fields in industry, business and computational science and engineering.