B.S. in Computer Science

4 Years On Campus Bachelors Program

University of Washington

Program Overview

The B.S. in Computer Science at the University of Washington’s Paul G. Allen School of Computer Science & Engineering combines a strong foundation in computing with opportunities to explore advanced areas such as artificial intelligence, machine learning, security, human-computer interaction, systems, and data science. It suits students who want to build, analyze, and apply computing systems while developing the technical and problem-solving skills needed for careers in technology, research, and other industries.

Curriculum Structure

First Year: Students begin with the mathematical, scientific, and programming foundations needed for computer science. CSE 121 Introduction to Computer Programming I, CSE 122 Introduction to Computer Programming II, and CSE 123 Introduction to Computer Programming III develop programming and computational-thinking skills, while mathematics and science requirements establish the broader technical foundation.

Second Year: Students progress into the core concepts underlying modern computing, including CSE 311 Foundations I, CSE 312 Foundations II, and CSE 332 Data Structures & Parallelism. They also study areas such as CSE 331 Software Design & Implementation and CSE 351 Hardware/Software Interface, strengthening their understanding of algorithms, software development, data structures, and how programs interact with computer hardware.

Third Year: Students move into advanced systems and software topics through courses such as CSE 333 Systems Programming, CSE 344 Data Management, and CSE 421 Introduction to Algorithms. Students can also begin tailoring their studies through areas such as CSE 446 Machine Learning, CSE 451 Introduction to Operating Systems, CSE 461 Computer Networks, or CSE 484 Computer Security.

Fourth Year: The final year provides substantial flexibility through senior electives and advanced computing courses, allowing students to develop deeper expertise in areas such as CSE 447 Natural Language Processing, CSE 455 Computer Vision, CSE 457 Computer Graphics, CSE 473 Artificial Intelligence, and CSE 478 Autonomous Robotics. Students interested in data science can complete the transcriptable Data Science Option, which includes CSE 421 Introduction to Algorithms, CSE 444 Database Systems Internals, CSE 446 Machine Learning, CSE 442 Data Visualization, and a Data & Society component.

Focus Areas: Artificial Intelligence, Machine Learning, Data Science, Human-Centered Computing, Software Engineering, Systems, Security, Computer Networks, Computer Graphics, Computer Vision, Natural Language Processing, Databases, Robotics, Embedded Systems, Web Development, Computational Biology, Quantum Computing, Digital Accessibility.

Learning Outcomes: Programming, computational thinking, algorithms, data structures, software design, data management, systems programming, computer architecture, machine learning, artificial intelligence, computer security, networks, human-computer interaction, data visualization, problem-solving, ethical and societal understanding of computing.

Professional Alignment (Accreditation) : Not stated for the B.S. in Computer Science. The Allen School states that its B.S. in Computer Engineering is accredited by the EAC Accreditation Commission of ABET, but this accreditation does not apply to the B.S. in Computer Science.

Reputation (Employability Rankings): The University of Washington’s Paul G. Allen School of Computer Science & Engineering states that it is consistently ranked among the top computer science programs in the nation. The school also reports that its graduates are major suppliers to leading technology companies including Microsoft, Amazon, and Google, while a majority of undergraduates participate in internships in Seattle’s technology sector.

Experiential Learning (Research, Projects, Internships etc.)

The BS in Computer Science at the University of Washington’s Paul G. Allen School of Computer Science & Engineering combines programming, software development, systems, data, and advanced computing with substantial hands-on work. Students can use dedicated instructional and research laboratories, work collaboratively on software and capstone projects, participate in undergraduate research, and gain experience with specialized computing hardware, development environments, robotics, graphics, databases, and other technologies.

Students develop these practical skills through:

Software engineering projects: CSE 403: Software Engineering uses a group project as its primary learning vehicle, covering requirements specification, software architecture, design, testing, software processes, and development tools.
Senior capstone projects: Allen School capstones require students to work in teams to define a substantial problem, design and implement a solution, produce a working artifact, and present the results through formal presentations and written reports. Current options include Embedded Systems Capstone, Accessibility Capstone, ML Capstone, Security Capstone, NLP Capstone, Games Capstone, and Human-AI Interaction Capstone.
Machine-learning research projects: CSE 481 M: ML Capstone places students in small groups of approximately three to complete an independent machine-learning research project, including developing research codebases, conducting experiments and analysis, and reporting results.
Security project work: CSE 481 S: Security Capstone has student teams create a computer-security product from conception and requirements through design, implementation, and evaluation, using practices such as threat modeling, penetration testing, and bug fixing.
Undergraduate research: CSE 494: Guided Research in Computer Science and Engineering provides initial research experience through projects completed individually or in small teams under experienced research mentors. Allen School undergraduates can also register for research with CSE faculty and affiliate faculty.
Computing laboratories: The Allen School operates four general-use instructional laboratories with approximately 150 PC workstations and capacity for more than 275 students, alongside five special-purpose laboratories with about 100 additional workstations.
Embedded Systems Project Laboratory: Students working with digital systems can use PC workstations, Tektronix logic analyzers, digital oscilloscopes, and other testing equipment for design, simulation, and hardware development.
Graphics and imaging facilities: Research and instructional resources include high-end graphics workstations, GPU compute clusters, Microsoft Kinect and Leap Motion controllers, Oculus Rift VR hardware, digital cameras, a 3D laser scanner, video projectors, and motion-control platforms.
Robotics laboratories: The Allen School supports robotics research across six laboratories with platforms including Franka Emika Panda, PR2, Fetch, Baxter, NAO, TurtleBot, Darwin-OP, Kinova Jaco 2, and Hebi robot arms, as well as custom-built robotic platforms.
Database and data-management tools: The Database Lab provides Windows and Linux workstations and access to systems including SQL Server, Spark, Hadoop, and Myria, supported by a high-performance cluster with substantial storage and memory resources.
Capstone laboratories: Four dedicated capstone labs can accommodate up to 90 PC workstations and support courses in areas such as accessibility, game design, operating systems, robotics, computer security, and virtual reality, with software and systems tailored to individual courses.
Collaborative learning spaces: The Allen Center and Gates Center provide breakout spaces, reservable meeting rooms, seminar rooms, laboratories for group-based experimental work, and project spaces designed to encourage collaboration between students, faculty, and researchers.
24/7 student computing and study support: The Allen School Study Center provides spaces for independent and collaborative work, while Allen School instructional labs are available to students 24 hours a day, 7 days a week.

Progression & Future Opportunities

The BS in Computer Science at the University of Washington’s Paul G. Allen School prepares graduates for technology careers across software, computing, and related industries, with software engineering identified by UW as the most common career path. Graduates can also apply their computing skills in sectors including health, retail, finance, aerospace, startups, and other technology-driven fields, while others continue into graduate education.

Typical career roles: Software Engineer, Software Developer, Computer Systems Engineer, Computing Researcher.

Career development and progression are supported through:

Allen School Career Resources: Students receive access to resume reviews, practice interviews, wage-negotiation guidance, career advising, the Allen School Career Board, TechTalks, annual recruiting events, and the undergraduate Resume Book, where industry-affiliate companies can search for candidates for internships and full-time positions.
Recruiting opportunities: The Allen School's recruiting events connect students directly with employers seeking interns and full-time employees; its 2026 fall recruiting event states that more than 1,400 CSE students and alumni typically participate in recruiting fairs.
Internships and co-ops: The Engineering Co-op & Internship Program supports undergraduate employment for 3-, 6-, or 9-month terms, during which students work full-time for a company and can receive academic credit while maintaining student status.
Research and employability: Undergraduate research can be completed for academic credit through CSE 496 and CSE 498, with objectives including applying knowledge from multiple courses, conducting research, producing technical documentation, and enhancing employability through evidence of independent work.
Employment outcomes: UW states that most Allen School graduates transition to industry positions, with software engineering being the most common route; the school also identifies Microsoft, Amazon, and Google among the leading technology employers of its graduates.
Salary figures: UW's official Allen School pages do not state a current average or median starting salary specifically for BS Computer Science graduates. Therefore, no unsupported salary figure is provided.
University–industry partnerships: The Allen School's Industry Affiliates include companies such as Meta, Google, Microsoft-affiliated technology organizations, Amazon-related regional technology networks, NVIDIA-related research ecosystem partners, Stripe, Uber, TikTok, Tesla, Nintendo, Snowflake, Databricks, Pinterest, and F5 Networks. These relationships support research collaborations, recruiting activities, technical talks, employer panels, and internship and employment opportunities.
Specific industry research: The Allen School highlights partnerships such as the Toyota Research Institute University Research Partnership, supporting research in AI, robotics, and driving, as well as the Center for the Future of Cloud Infrastructure (FOCI), which works with industry on next-generation cloud infrastructure.
Accreditation value: UW's official ABET page states that Computer Engineering, rather than the BS Computer Science program, is accredited by ABET. The BS Computer Science program should therefore not be described as ABET-accredited based on the university's current official information.
Graduation and long-term progression: The Allen School offers a Combined B.S./M.S. program, allowing eligible students to continue from undergraduate study into advanced computer science coursework. UW also provides dedicated graduate-school resources for students considering academic careers and further study.

Further Academic Progression: After completing the BS in Computer Science, students can pursue a Master of Science, including UW's Combined B.S./M.S. pathway, or continue into a Ph.D. in Computer Science & Engineering or another specialized computing-related graduate program. Students interested in research careers can also use the undergraduate research experience as preparation for doctoral study, while those focused on industry can enter employment directly or gain additional specialization through graduate education.