Computer Science, BS
Degree: Bachelor of Science (BS)
Major: Computer Science
Program Overview
The Bachelor of Science degree program in computer science is designed to give a student a strong background in the fundamentals of mathematics and computer science. The curriculum is designed according to the latest ACM/IEEE computer science curriculum guidelines. A graduate of this program should be able to use these fundamentals to analyze and evaluate software systems and the underlying abstractions upon which they are based. A graduate should also be able to design and implement software systems that are state-of-the-art solutions to a variety of computing problems; this includes problems that are sufficiently complex to require the evaluation of design alternatives and engineering trade-offs. In addition to these program-specific objectives, students can use their technical and open electives to pursue interests in software engineering, algorithms, artificial intelligence, databases, data mining, bioinformatics, security, computer systems, and computer networks, and all students in the Case School of Engineering are exposed to societal issues, professionalism, and are provided opportunities to develop leadership skills.
The Bachelor of Science degree program in Computer Science is accredited by the Computing Accreditation Commission of ABET, under the commission’s General Criteria and Program Criteria for Computer Science and Similarly Named Computing Programs.
Mission
The mission of the Bachelor of Science degree program in computer science is to graduate students who have fundamental technical knowledge of their profession and the requisite technical breadth and communications skills to become leaders in creating the new techniques and technologies which will advance the field of computer science and its application to other disciplines.
Program Educational Objectives
Graduates from the Bachelor of Science in Computer Science program will be prepared to:
- Analyze real-world problems and create solutions based on the fundamentals of computer science and mathematics.
- Work effectively, professionally, collaboratively, and ethically.
- Assume leadership roles in industry, academia, public service, and entrepreneurship.
- Successfully progress in advanced degree programs in computing and related fields.
Learning Outcomes
As preparation for achieving the above educational objectives, the Bachelor of Science degree program in computer science is designed so that students attain the ability to:
- Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
- Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.
- Communicate effectively in a variety of professional contexts.
- Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
- Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
- Apply computer science theory and software development fundamentals to produce computing-based solutions.
Co-op and Internship Programs
Opportunities are available for students to alternate studies with work in industry or government as a co-op student, which involves paid full-time employment over seven months (one semester and one summer). Students may work in one or two co-ops, beginning in the third year of study. Co-ops provide students the opportunity to gain valuable hands-on experience in their field by completing a significant engineering project while receiving professional mentoring. During a co-op placement, students do not pay tuition but maintain their full-time student status while earning a salary. Alternatively or additionally, students may obtain employment as summer interns.
Undergraduate Policies
For undergraduate policies and procedures, please review the Undergraduate Academics section of the General Bulletin.
Combined Bachelor's/Master's Programs
Undergraduate students may participate in accelerated programs toward graduate or professional degrees. For more information and details of the policies and procedures related to accelerated studies, please visit the Undergraduate Academics section of the General Bulletin.
Program Requirements
Students seeking to complete this major and degree program must meet the general requirements for bachelor's degrees and the Unified General Education Requirements. Students completing this program as a secondary major while completing another undergraduate degree program do not need to satisfy the school-specific requirements associated with this major.
Each student is required to complete at least 20 computer science and computer science related courses totaling at least 63 credit hours plus additional courses in mathematics, science, engineering and statistics.
The 20 computer science and computer science related courses must include:
- all six core courses;
- at least two courses from each of the four breadth areas;
- and a course from the secure computing requirement list.
The remaining courses needed to fulfill the 20 course and 63 credit hour requirement may come from the list of approved technical electives with at most two Group 2 courses.
Other computer science related courses not listed here may be used with prior permission from the student’s academic advisor.
Computer Science Core Requirement
| Code | Title | Credit Hours |
|---|---|---|
| Required Core Courses: | ||
| CSDS 132 | Programming in Java | 3 |
| or CSDS 134 & CSDS 235 | Programming in Python and The Java Programming Language | |
| CSDS 233 | Introduction to Data Structures | 4 |
| CSDS 281 | Logic Design and Computer Organization | 4 |
| CSDS 302 | Discrete Mathematics | 3 |
| CSDS 310 | Algorithms | 3 |
| CSDS 395 | Senior Project in Computer Science | 4 |
Computer Science Breadth Requirement
BS students are required to complete at least two courses from each of the four breadth areas for a total of eight computer science breadth courses.
| Code | Title | Credit Hours |
|---|---|---|
| Breadth Area 1 | ||
| Choose two of the following: | ||
| CSDS 341 | Introduction to Database Systems | 3 |
| CSDS 356 | Data Privacy | 3 |
| CSDS 390 | Advanced Game Development Project | 3 |
| CSDS 393 | Software Engineering | 3 |
| Breadth Area 2 | ||
| Choose two of the following: | ||
| CSDS 312 | Introduction to Data Science Systems | 3 |
| CSDS 314 | Computer Architecture | 3 |
| CSDS 325 | Computer Networks I | 3 |
| CSDS 338 | Intro to Operating Systems and Concurrent Programming | 4 |
| Breadth Area 3 | ||
| Choose two of the following: | ||
| CSDS 337 | Compiler Design | 4 |
| CSDS 343 | Theoretical Computer Science | 3 |
| CSDS 344 | Computer Security | 3 |
| CSDS 345 | Programming Language Concepts | 3 |
| Breadth Area 4 | ||
| Choose two of the following: | ||
| CSDS 313 | Introduction to Data Analysis | 3 |
| CSDS 330 | Introduction to Artificial Intelligence | 3 |
| CSDS 335 | Data Mining for Big Data | 3 |
| CSDS 340 | Introduction to Machine Learning | 3 |
Computer Science Secure Computing Requirement
Students pursuing the BS degree must demonstrate competence in the principles and practices of secure computing by completing one of the following courses as part of their 20 computer science or computer science related courses. This course may be double counted as a computer science breadth course or technical elective course, as appropriate.
| Code | Title | Credit Hours |
|---|---|---|
| Required Secure Computing Course: | ||
| Choose one of the following: | ||
| CSDS 344 | Computer Security | 3 |
| CSDS 356 | Data Privacy | 3 |
| CSDS 427 | Internet Security and Privacy | 3 |
| CSDS 444 | Computer Security | 3 |
| CSDS 448 | Smartphone Security | 3 |
| MATH 408 | Introduction to Cryptology | 3 |
Mathematics and Engineering Requirement
| Code | Title | Credit Hours |
|---|---|---|
| Required Mathematics, Science and Engineering Courses: | ||
| ENGR 399 | Impact of Engineering on Society | 3 |
| MATH 121 | Calculus for Science and Engineering I | 4 |
| MATH 122 | Calculus for Science and Engineering II | 4 |
| or MATH 124 | Calculus II | |
| MATH 201 | Introduction to Linear Algebra for Applications | 3 |
| or MATH 307 | Linear Algebra | |
| MATH 223 | Calculus for Science and Engineering III | 3 |
| or MATH 227 | Calculus III | |
Science Requirement
The Science Requirement can be satisfied by completing one of the sequences listed below. Students wishing to combine CS with other science disciplines can alternatively satisfy the Science Requirement either by completing one of the following minor programs: Biology, Chemistry, or Geological Sciences; or by completing one of the following major programs: Biology, Biochemistry, Chemistry, Geological Sciences, or Neuroscience.
| Code | Title | Credit Hours |
|---|---|---|
| Choose one of the following: | 4 | |
| Introductory Physics I | ||
| General Physics I - Mechanics | ||
| Physics and Frontiers I - Mechanics | ||
| Choose one of the following: | 4 | |
| Introductory Physics II | ||
| General Physics II - Electricity and Magnetism | ||
| Physics and Frontiers II - Electricity and Magnetism | ||
Statistics Requirement
| Code | Title | Credit Hours |
|---|---|---|
| Required Statistics Course: | ||
| Choose one of the following: | ||
| MATH 380 | Introduction to Probability | 3 |
| OPRE 207 | Statistics for Business and Management Science I | 3 |
| STAT 302 | Introduction to Statistical Inference | 3 |
| STAT 312 | Basic Statistics for Engineering and Science | 3 |
| STAT 313 | Statistics for Experimenters | 3 |
| STAT 332 | Statistics for Signal Processing | 3 |
| STAT 333 | Uncertainty in Engineering and Science | 3 |
List of Approved Technical Electives
This list of approved technical electives is divided into groups according to how closely a course is related to the core knowledge areas as defined in the ACM/IEEE computer science curriculum guidelines. Computer Science BS students may use up to two courses from Group 2 as technical electives toward the computer science degree. Computer science related courses not listed below may be used as a technical elective but require prior permission from the student’s academic advisor.
Group 1
| Code | Title | Credit Hours |
|---|---|---|
| Any CSDS Course | ||
| ECSE 301 | Digital Logic Laboratory | 2 |
| ECSE 303 | Embedded Systems Design and Laboratory | 3 |
| ECSE 315 | Digital Systems Design | 4 |
| ECSE 317 | Computer Design - FPGAs | 3 |
| ECSE 323 | Introduction to Human-Robot Interaction | 3 |
| ECSE 373 | Introduction to Modern Robotics | 4 |
| ECSE 419 | Computer System Architecture | 3 |
| ECSE 484 | Computational Intelligence I: Basic Principles | 3 |
| ECSE 485 | VLSI Systems | 3 |
| ECSE 488 | Embedded Systems Design | 3 |
| MATH 330 | Introduction to Scientific Computing | 3 |
| MATH 356 | Math in Machine Learning | 3 |
| MATH 382 | High Dimensional Probability | 3 |
| MATH 406 | Mathematical Logic and Model Theory | 3 |
| MATH 408 | Introduction to Cryptology | 3 |
| MATH 431 | Introduction to Numerical Analysis I | 3 |
| MATH 444 | Mathematics of Data Mining and Pattern Recognition | 3 |
| MATH 473 | Introduction to Mathematical Image Processing and Computer Vision | 3 |
| PHIL 306 | Mathematical Logic and Model Theory | 3 |
| PHIL 393 | Ethics of Artificial Intelligence and Emerging Technology | 3 |
Group 2
| Code | Title | Credit Hours |
|---|---|---|
| DSCI 330 | Cognition and Computation | 3 |
| DSCI 351 | Exploratory Data Science | 3 |
| DSCI 352 | Applied Data Science Research | 3 |
| DSCI 353 | Statistical and Machine Learning for Inference, Prediction and Reasoning | 3 |
| ECON 380 | Computational Methods for Economic Modeling | 1.5 |
| ECSE 245 | Electronic Circuits | 4 |
| ECSE 246 | Signals and Systems | 4 |
| ECSE 304 | Control Engineering I with Laboratory | 3 |
| ECSE 305 | Control Engineering I Laboratory | 1 |
| ECSE 309 | Electromagnetic Fields I | 3 |
| ECSE 313 | Signal Processing | 3 |
| ECSE 318 | VLSI/CAD | 4 |
| ECSE 319 | Applied Probability and Stochastic Processes for Biology | 3 |
| ECSE 324 | Modeling and Simulation of Continuous Dynamical Systems | 3 |
| ECSE 346 | Engineering Optimization | 3 |
| ECSE 350 | Operations and Systems Design | 3 |
| ECSE 354 | Digital Communications | 3 |
| ECSE 375 | Applied Control | 3 |
| ECSE 408 | Introduction to Linear Systems | 3 |
| ECSE 413 | Nonlinear Systems I | 3 |
| ECSE 414 | Wireless Communications | 3 |
| ECSE 416 | Convex Optimization for Engineering | 3 |
| ECSE 489 | Robotics I | 3 |
| ENGR 210 | Introduction to Circuits and Instrumentation | 4 |
| MATH 224 | Elementary Differential Equations | 3 |
| MATH 228 | Differential Equations | 3 |
| MATH 303 | Elementary Number Theory | 3 |
| MATH 308 | Introduction to Abstract Algebra | 3 |
| MATH 327 | Convexity and Optimization | 3 |
| MATH 413 | Graph Theory | 3 |
| MATH/STAT 437 | Introduction to Stochastic Processes | 3 |
| MATH 439 | Bayesian Scientific Computing | 3 |
| PHIL 201 | Introduction to Logic | 3 |
| PHYS 221 | Introduction to Modern Physics | 3 |
| PHYS 250 | Computational Methods in Physics | 3 |
| STAT 327 | Statistical Computing | 3 |
| STAT 346 | Mathematical Statistics | 3 |
Sample Plan of Study
| First Year | ||
|---|---|---|
| Fall | Credit Hours | |
| CSDS 132 | Programming in Java | 3 |
| MATH 121 | Calculus for Science and Engineering I | 4 |
| Academic Inquiry Seminar, Breadth, or Elective course a | 3 | |
| Open Elective | 4 | |
| Credit Hours | 14 | |
| Spring | ||
| CSDS 233 | Introduction to Data Structures | 4 |
| MATH 122 or MATH 124 | Calculus for Science and Engineering II or Calculus II | 4 |
| PHYS 121 | General Physics I - Mechanics | 4 |
| Academic Inquiry Seminar, Breadth, or Elective course a | 3 | |
| Credit Hours | 15 | |
| Second Year | ||
| Fall | ||
| CSDS 281 | Logic Design and Computer Organization | 4 |
| CSDS 302 | Discrete Mathematics | 3 |
| MATH 223 or MATH 227 | Calculus for Science and Engineering III or Calculus III | 3 |
| PHYS 122 | General Physics II - Electricity and Magnetism | 4 |
| Breadth, or Elective course a | 3 | |
| Credit Hours | 17 | |
| Spring | ||
| MATH 201 or MATH 307 | Introduction to Linear Algebra for Applications or Linear Algebra | 3 |
| Breadth, or Elective course a | 3 | |
| Computer Science Breadth course | 3 | |
| Statistics Elective | 3 | |
| Technical Elective | 3 | |
| Credit Hours | 15 | |
| Third Year | ||
| Fall | ||
| CSDS 310 | Algorithms | 3 |
| Breadth, or Elective course a | 3 | |
| Computer Science Breadth course | 3 | |
| Computer Science Breadth course | 3 | |
| Technical Elective | 3 | |
| Credit Hours | 15 | |
| Spring | ||
| ENGR 399 | Impact of Engineering on Society | 3 |
| Breadth, or Elective course a | 3 | |
| Computer Science Breadth course | 3 | |
| Computer Science Breadth course | 3 | |
| Computer Science Breadth course | 3 | |
| Credit Hours | 15 | |
| Fourth Year | ||
| Fall | ||
| Breadth, or Elective course a | 3 | |
| Computer Science Breadth course | 3 | |
| Open Elective | 3 | |
| Technical Elective | 3 | |
| Technical Elective | 3 | |
| Credit Hours | 15 | |
| Spring | ||
| CSDS 395 | Senior Project in Computer Science | 4 |
| Breadth, or Elective course a | 3 | |
| Computer Science Breadth course | 3 | |
| Technical Elective | 3 | |
| Technical Elective | 3 | |
| Credit Hours | 16 | |
| Total Credit Hours | 122 | |