Overview

The department uses a standard numbering scheme for all courses. The course levels are consistent with Georgetown University's numbering scheme. Course numbers within each of these levels are based on the ACM Taxonomy. The table below shows the department's course numbering system. The first digit of the course's number represents its overall level of difficulty.

Georgetown's Course Numbering System.

Range Type/Topic
001–199 Undergraduate Only
200–299 Upperclass Undergraduate
300–349 Undergraduate Tutorials, Readings, Research
350–399 Reserved
400–499 Upperclass Undergraduate & Graduate
500–699 Graduate Lectures
700–799 Graduate Seminars and Topics Courses
800–899 Doctoral Seminars
900–998 Graduate Research, Tutorials, Readings
999 Thesis Research

The table below shows the department's scheme for numbering courses based on the ACM Taxonomy. The second digit of a course number identifies the area of computer science to which the course pertains. For example, courses in the range X40–X49 are about theory, algorithms, and the mathematics of computing. The department's undergraduate course on algorithms has the number 240, whereas the graduate-level course on algorithms has the number 540.

Course Numbering System Based on the ACM Taxonomy.

Range Type/Topic
X00–X19 Introductory, Applications, Millieux, Miscellaneous
X20–X29 Hardware, Systems, Organization
X30–X39 Security
X40–X49 Theory, Algorithms, Mathematics of Computing
X50–X59 Software/Software Engineering
X60–X69 Data
X70–X79 Computing Methodologies
X80–X89 Information Technology and Systems
X90–X99 Interdisciplinary Topics

The department instituted this new course numbering system in 2011. The new and old course numbers and the course title appear in the table below.

New and Old Course Numbers.

New Old Title
010 010 Introduction to Information Technology
011 011 Introduction to Information Privacy
012 012 Introduction to Media Computing
014 014 Introduction to Information Systems
015 015 Introduction to Computer Science Using Ruby
030 127 Mathematical Methods of Computer Science
051 071 Computer Science I
052 072 Computer Science II
120 250 Computer Hardware Fundamentals
121 251 Computer Systems Fundamentals
150 175 Advanced Programming
160 173 Data Structures
225 390 Networks and Data Communications
230 352 Information Assurance
235 353 Introduction to Network Security
240 330 Introduction to Algorithms
245 385 Theory of Computation
252 272 Programming Languages
255 374 Operating Systems
258 355 Software Engineering
260 350 Codes and Ciphers
270 387 Artificial Intelligence
275 282 Computer Graphics
280 380 Introduction to Databases
285 382 Introduction to Data Mining
317 317 Unix for Non-believers
411 511 Information Warfare
428 393 Wireless Networks
470 360 Introduction to Computer Simulation and Modeling
488 416 Information Retrieval
520 560 Computer Hardware and Systems Architecture
522 566 Non-Standard Computing
535 555 Network Security
538 552 Intrusion and Anomaly Detection
540 531 Advanced Algorithms
560 545 Cryptography
575 688 Machine Learning
580 580 Advanced Database Systems
585 585 Knowledge Discovery and Data Mining
586 N/A Text Mining & Analysis
730 755 Topics in Computer Security
780 716 Topics in Information Systems