Course Numbering System

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

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.

Course Numbering System Based on the ACM Taxonomy
Range Type/Topic
X00-X19

Introductory, Applications, Milieux, 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 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

372

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

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