Computer science involves the understanding, use, and extension of computational ideas and their implementation. A Northwestern computer science graduate will
- Comprehend the breadth of computer science, its key intellectual divisions and questions, and its past and likely future influence on engineering, science, medicine, business, and law
- Approach problems from the algorithmic perspective, understanding the nature and broad reach of computation and how to apply it abstractly
- Approach problems from the systems perspective, understanding the evolving layers of the software/hardware stack and how to create, use, and extend them
- Approach problems from the perspective of artificial intelligence, understanding how to make progress in solving seemingly intractable problems
- Design and implement complex software systems, individually and as a team member
- Design and implement effective human-machine interfaces
Courses and undergraduate research opportunities focus on software, ranging from theoretical models to practical applications. They establish a common breadth of knowledge in computer science, allowing students flexibility in areas in which they choose to specialize, such as
- Artificial intelligence, including mobile robots with perceptual systems, models of memory and reasoning, knowledge representation, natural-language comprehension, planning, and problem solving
- Computer systems, including parallel, distributed, and real-time systems, performance evaluation, prediction, and scheduling
- Networked systems, including peer-to-peer computing, large-scale data storage, network security, and pervasive computing environments
- Programming languages and compilers, including semantics, optimization, and software
- Human-computer interaction, including interface design, task modeling, intelligent interfaces, and authoring tools
- Distributed interactive systems, including client-server and web-based applications such as heterogeneous databases and multimedia learning environments
- Theoretical computer science, focusing on algorithm design and analysis of algorithms’ worst- and average-case behavior
- Intelligent information systems, including “frictionless” proactive systems and context- and task-sensitive retrieval systems
- Computer graphics and human-computer interfaces for spatial applications, visualization, and computer entertainment
COMP_SCI 101-0 Computer Science: Concepts, Philosophy, and Connections (1 Unit) General introduction to historical and current intellectual questions in computer science. Theory, systems, artificial intelligence, interfaces, software development, and interactions with business, politics, law, medicine, engineering, and other sciences. Social Behavioral Sciences Distro Area
COMP_SCI 110-0 Introduction to Computer Programming (1 Unit) Introduction to programming practice using a modern programming language. Analysis and formulation of problems for computer solution. Systematic design, construction, and testing of programs. Substantial programming assignments. Not to be taken for credit with or after COMP_SCI 111-0. Formal Studies Distro Area
COMP_SCI 111-0 Fundamentals of Computer Programming (1 Unit) Fundamental concepts of computer programming with heavy emphasis on design of recursive algorithms and test-driven development. Functional, imperative, and object-oriented programming paradigms. Procedural abstraction, data abstraction, and modularity. Required for the computer science degree. Formal Studies Distro Area
COMP_SCI 150-0 Fundamentals of Computer Programming 1.5 (1 Unit) An introduction to Object-oriented programming: focus on Python but including a brief introduction to a statically typed language (e.g. C++). Students will use some approaches from Artificial Intelligence and Machine Learning to complete programming assignments. Required for the computer science degree. Prerequisite: COMP_SCI 110-0 or COMP_SCI 111-0.
COMP_SCI 211-0 Fundamentals of Computer Programming II (1 Unit) Programming in statically-typed imperative languages. The von Neuman machine model: pointers, address manipulation, and manual memory management. Object-oriented programming and design. The C/C++ language family. Required for the computer science degree. Not to be taken for credit with COMP_SCI 230-0. Prerequisite: COMP_SCI 111-0 or COMP_SCI 150-0.
COMP_SCI 212-0 Mathematical Foundations of Comp Science (1 Unit) Basic concepts of finite and structural mathematics. Sets, axiomatic systems, the propositional and predicate calculi, and graph theory. Application to computer science: sequential machines, formal grammars, and software design. Prerequisite: MATH 228-1.
COMP_SCI 213-0 Introduction to Computer Systems (1 Unit) The hierarchy of abstractions and implementations that make up a modern computer system; demystifying the machine and the tools used to program it; systems programming in C in the UNIX environment. Preparation for upper-level systems courses. Prerequisite: COMP_SCI 211-0.
COMP_SCI 214-0 Data Structures & Algorithms (1 Unit) Design, implementation, and performance analysis of abstract data types; data structures and their algorithms. Topics include fundamental collection classes, tree and graph representations and walks, search trees, sorting, priority queues and heaps, least-cost paths computations, and disjoint-set structures. Required for the computer science degree. Prerequisite: COMP_SCI 111-0 and (COMP_SCI 211-0 or COMP_SCI 150-0).
COMP_SCI 217-0 Data Management & Information Processing (1 Unit) This class offers a hands-on introduction to data representation, data modelling, and the SQL language for accessing and analyzing data in relational databases. Students access and analyze data in real-world large-scale databases from the public domain. Not for computer science or computer engineering degree candidates. Prerequisite: COMP_SCI 110-0 or COMP_SCI 111-0 or permission of instructor.
COMP_SCI 230-0 Programming for Engineers (1 Unit) Introduction to computer programming in an object-oriented language. Emphasis on applications to computer systems, computer simulation, and discrete optimization. Basic principles of software engineering. Not to be taken for credit with or after COMP_SCI 211-0. Prerequisites: GEN_ENG 205-1, GEN_ENG 205-2.
COMP_SCI 295-0 Special Topics in Computer Science (1 Unit) Topics suggested by students or faculty and approved by the department.
COMP_SCI 301-0 Introduction to Robotics Laboratory (1 Unit) Lab-based introduction to robotics, focusing on hardware (sensors/ actuators) and software (sensor processing/behavior development); motion control and planning; artificial intelligence; machine learning. Not open to graduate students except by consent of instructor. Prerequisite: COMP_SCI 110-0, COMP_SCI 111-0, or consent of instructor.
COMP_SCI 310-0 Scalable Software Architectures (1 Unit)
Teaches software design principles for building high-scale Internet services. Focuses on challenges arising when assembling software services that run on many machines in parallel and which require the coordination of multiple software applications.
COMP_SCI 313-0 Tangible Interaction Design and Learning (1 Unit) The use of tangible interaction to create innovative learning experiences, including distributed cognition, embodied interaction, cultural forms, and design frameworks. Prerequisite: COMP_SCI 110-0.
COMP_SCI 314-0 Technology and Human Interaction (1 Unit)
Understanding human interactions that occur both with and through technology; design, creation, and evaluation of technologies to support such interactions.
COMP_SCI 315-0 Design, Technology, and Research (1 Unit)
Hands-on experience in the research learning environment. Students lead research projects in social and crowd computing, cyber-learning, human-computer interaction, and artificial intelligence.
Prerequisite: consent of instructor (by application only).
COMP_SCI 321-0 Programming Languages (1 Unit)
Introduction to key parts of programming languages: syntax, semantics, and pragmatics. Implementation of a series of interpreters that show how various aspects of programming languages behave.
COMP_SCI 322-0 Compiler Construction (1 Unit)
The compiler is the programmer's primary tool. Understanding the compiler is therefore critical for programmers, even if they never build one. Furthermore, many design techniques that emerged in the context of compilers are useful for a range of other application areas. This course introduces students to the essential elements of building a compiler: parsing, context-sensitive property checking, code linearization, register allocation, etc. To take this course, students are expected to already understand how programming languages behave, to a fairly detailed degree. The material in the course builds on that knowledge via a series of semantics preserving transformations that start with a fairly high-level programming language and culminate in machine code.
Prerequisite: COMP_SCI 213-0.
COMP_SCI 323-0 Code Analysis and Transformation (1 Unit)
Prerequisite: COMP_SCI 213-0.
COMP_SCI 325-1 Artificial Intelligence Programming (1 Unit)
Introduction to LISP and programming knowledge-based systems and interfaces. Strong emphasis on writing maintainable, extensible systems. Topics include semantic net-works, frames, pattern matching, deductive inference rules, case-based reasoning, and discrimination trees. Project-driven. Substantial programming assignments.
COMP_SCI 330-0 Human Computer Interaction (1 Unit)
Introduction to human-computer interaction and design of systems that work for people and their organizations. Understanding the manner in which humans interact with and use computers for productive work.
Prerequisite: programming experience.
COMP_SCI 331-0 Introduction to Computational Photography (1 Unit)
Fundamentals of digital imaging and modern camera architectures. Hands-on experience acquiring, characterizing, and manipulating data captured using a modern camera platform.
COMP_SCI 335-0 Introduction to the Theory of Computation (1 Unit)
Mathematical foundations of computation, including computability, relationships of time and space, and the P vs. NP problem.
Prerequisite: COMP_SCI 212-0 or consent of instructor.
COMP_SCI 336-0 Design & Analysis of Algorithms (1 Unit)
Analysis techniques: solving recurrence equations. Algorithm design techniques: divide and conquer, the greedy method, backtracking, branch-and-bound, and dynamic programming. Sorting and selection algorithms, order statistics, heaps, and priority queues.
COMP_SCI 337-0 Natural Language Processing (1 Unit)
Semantics-oriented introduction to natural language processing, broadly construed. Representation of meaning and knowledge inference in story understanding, script/frame theory, plans and plan recognition, counter-planning, and thematic structures.
Prerequisite: COMP_SCI 348-0 or consent of instructor.
COMP_SCI 338-0 Practicum in Intelligent Information Systems (1 Unit)
A practical excursion into building intelligent information systems. Students develop a working program in information access, management, capture, or retrieval. Project definition, data collection, technology selection, implementation, and project management.
COMP_SCI 339-0 Introduction to Database Systems (1 Unit)
Data models and database design. Modeling the real world: structures, constraints, and operations. The entity relationship to data modeling (including network hierarchical and object-oriented), emphasis on the relational model. Use of existing database systems for the implementation of information systems.
COMP_SCI 340-0 Introduction to Networking (1 Unit)
A top-down exploration of networking using the five-layer model and the TCP/IP stack, covering each layer in depth. Students build web clients, servers, and a TCP implementation and implement routing algorithms.
COMP_SCI 341-0 Mechanism Design (1 Unit)
Applying algorithms and microeconomics to derive a theory of the design of mechanisms that produce desired outcomes despite counteractive inputs by outside agents. Key application areas: auctions, markets, networking protocols.
COMP_SCI 343-0 Operating Systems (1 Unit)
Fundamental overview of operating systems, including: concurrency (processes, synchronization, semaphores, monitors, deadlock); memory management (segmentation, paging virtual memory policies); software system architectures (level structures, microkernals); file systems (directory structures, file organization, RAID); protection (access control, capabilities, encryption, signatures, authentication). Requires substantial programming projects.
COMP_SCI 344-0 Design of Computer Problem Solvers (1 Unit)
Principles and practice of organizing and building artificial intelligence reasoning systems. Pattern-directed rule systems, truth-maintenance systems, and constraint languages.
COMP_SCI 345-0 Distributed Systems (1 Unit)
Basic principles behind distributed systems (collections of independent components that appear to users as a single coherent system) and main paradigms used to organize them.
COMP_SCI 348-0 Introduction to Artificial Intelligence (1 Unit)
Core techniques and applications of AI. Representing, retrieving, and applying knowledge for problem solving. Hypothesis exploration. Theorem proving. Vision and neural networks.
COMP_SCI 349-0 Machine Learning (1 Unit)
Study of algorithms that improve through experience. Topics typically include Bayesian learning, decision trees, genetic algorithms, neural networks, Markov models, and reinforcement learning. Assignments include programming projects and written work.
Prerequisite: COMP_SCI 348-0.
COMP_SCI 350-0 Introduction to Computer Security (1 Unit)
Basic principles and practices of computer and information security. Software, operating system, and network security techniques, with detailed analysis of real-world examples. Topics include cryptography, authentication, software and operating system security (e.g., buffer overflow), Internet vulnerability (DoS attacks, viruses/worms, etc.), intrusion detection systems, firewalls, VPN, and web and wireless security.
COMP_SCI 351-1 Introduction to Computer Graphics (1 Unit)
Mathematical software and hardware requirements for computer graphics systems. Data structures and programming languages. Random displays. Graphic applications.
Prerequisite: COMP_SCI 214-0.
COMP_SCI 351-2 Intermediate Computer Graphics (1 Unit)
Methods and theory of computer graphics. Project-oriented approach. Describing shapes, movement, and lighting effects; interactive elements.
COMP_SCI 352-0 Machine Perception of Music & Audio (1 Unit)
Machine extraction of musical structure in audio and MIDI and score files, covering areas such as source separation and perceptual mapping of audio to machine-quantifiable measures.
COMP_SCI 354-0 Computer System Security (1 Unit)
The past decade has seen an explosion in the concern for the security of information. This course introduces students to the basic principles and practices of computer system and networking security, with detailed analysis of real-world examples and hands-on practice. Topics include the basic crypto, authentication, reverse engineering, buffer overflow attacks, vulnerability scanning, web attacks, firewalls, intrusion detection/prevention systems, etc. We will first introduce the basic theory for each type of attack; then we will actually carry them out in 'real-world' settings. The goal is to learn security by learning how to view your machine from a hacker's perspective. In addition, we encourage students to participate in the UCSB International Capture the Flag Competition. Capture the Flag is a network security exercise where the goal is to exploit other machines while defending your own. In fact, this course should prepare you for any one of many capture the flag competitions that take place year-round. We will learn about different types of hacks and perform them. After learning how to execute such exploits and penetrate a network, we will discuss ways to protect a network from others exploiting the same vulnerabilities. Understanding security is essential in all fields of software development and computing. For major or minors in Computer Science, this course can satisfy the system breadth.
COMP_SCI 355-0 Digital Forensics and Incident Response (1 Unit)
COMP_SCI 367-0 Wireless and Mobile Health: Passive Sensing Data Analytics (1 Unit)
A hands-on introduction and experience to the growing field of mobile Health. Students work together on a project with clinicians and faculty in medicine, building a unique mHealth system while testing their system on a small population. Theory-driven project hypothesis, technology selection and development, passive sensing data analytic chain understanding and implementation, and project management.
COMP_SCI 370-0 Computer Game Design (1 Unit)
Plot, narrative, and character simulation for creating game worlds; artificial intelligence for synthetic characters; tuning gameplay. Substantial programming and project work.
COMP_SCI 371-0 Knowledge Representation and Reasoning (1 Unit)
Principles and practices of knowledge representation, including logics, ontologies, commonsense knowledge, and semantic web technologies.
COMP_SCI 372-0 Designing & Constructing Models with Multi-Agent Language (1 Unit) Exploration and analysis of multi-agent models, which simulate "emergent" scientific phenomena in a wide variety of content domains.
COMP_SCI 376-0 Computer Game Design and Development (1 Unit)
Introduction to design of simulation-based media, with an emphasis on 2D game design. Mathematical preliminaries: linear, affine, and projective spaces, linear transforms, inner and exterior products, unit quaternions; Architecture: update/render loop, component systems, serialization and deserialization, event handling and asynchronous processing, multitasking; Rendering: scene graphs, meshes, shaders, sprites; Networking; Audio; Physics: particles, rigid bodies, collision detection; Gameplay design.
Prerequisite: COMP_SCI 214-0.
COMP_SCI 377-0 Game Design Studio (1 Unit)
In this course, students will design and develop games using the Unity game engine, with focus on team-based projects and agile development practices. Lectures will cover game design theory, game architecture and implementation, and the business of game development. Students will participate in class discussion and evaluation of projects in progress, to develop their skills in iterative design and implementation.
Prerequisite: COMP_SCI 376-0.
COMP_SCI 393-0 Software Construction (1 Unit)
Building software is a craft that requires careful design. This course teaches software design principles in a studio setting. Each week, students present their programs to the class for review. Together, the class evaluates the programs for correctness and, more importantly, clarity and design. Expect to learn how to build reliable, maintainable, extensible software and how to read others' codes.
COMP_SCI 394-0 Agile Software Development (1 Unit)
Developing mobile and web applications, using modern sustainable agile practices, such as backlogs, user stories, velocity charts, and test driven development, to deliver value as quickly as possible to end users, clients, developers, and the development organization.
COMP_SCI 396-0 Special Topics in Computer Science (1 Unit)
Projects suggested by faculty and approved by the department. Equivalent to 397 but intended to apply toward courses for the computer science major and its project requirement.
COMP_SCI 397-0 Special Projects in Computer Science (1 Unit)
Topics suggested by faculty and approved by the department. Equivalent to 396 but intended to apply toward courses for the computer science major.
COMP_SCI 399-0 Projects (1 Unit) Seminar and projects for advanced undergraduates on subjects of current interest in electrical and computer engineering.