Global Arc

COS 333I offers AB COS concentrators an option for completing one semester of independent work. As such, it does not carry course credit but it does follow the structure and format of the course COS 333. By taking this course not-for-credit, students in COS 333I will have the opportunity to develop their programming skills by working on their own code and in group projects to satisfy the JIW requirement for the semester in which they are enrolled. The cumulative grade for this work will be reflected on students' transcripts as COS 981.

This course introduces algorithms for analyzing DNA, RNA, and protein, the three fundamental molecules in the cell. Students will learn algorithms on strings, trees, and graphs, and their applications in: sequence comparison and alignment; molecular evolution and comparative genomics; DNA sequencing and assembly; recognition of genes and regulatory elements; and RNA structure and protein interaction networks. Students will also implement algorithms and apply them to biological data. Prerequisites: COS 126, COS 226. Some exposure to discrete math and basic probability (e.g., COS 240*)

An introduction to computer architecture and organization. Instruction set design; basic processor implementation techniques; caches and virtual memory; CPUs, GPUs, storage systems, hardware-software APIs, and compilers. Goal: building understanding of the systems you design and program. Design trade-offs among cost, performance, complexity, and power dissipation. Prerequisite: COS 217.

This single-term one-on-one IW course (COS 398) requires students to complete a substantial research project under the advisement of a Princeton faculty member. The work requires consistent engagement throughout the term. Students may pursue a project aligned with their interests and skills. The work must result in a final paper. Offered in the fall, this course provides AB and BSE juniors with an opportunity to concentrate on a state-of-the-art computer science project to fulfill the IW requirement.

This single-term one-on-one IW course (COS 399) requires students to complete a substantial research project under the advisement of a Princeton faculty member. The work requires consistent engagement throughout the term. Students may pursue a project aligned with their interests and skills. The work must result in a final paper. Offered in the spring, this course provides AB & BSE juniors with an opportunity to concentrate on a state-of-the-art computer science project to fulfill the IW requirement.

This course covers the design and implementation of distributed systems. Students will gain an understanding of the principles and techniques behind the design of modern, reliable, and high-performance distributed systems. Topics: server design, network programming, naming, concurrency and locking, consistency models and techniques, security, and fault tolerance. Modern techniques and systems employed at some of the largest Internet sites will also be covered. Students will gain practical experience designing, implementing, and debugging real distributed systems through programming assignments. Prereqs: COS 217 required; COS 316 rec.

Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms. Introduction to NP-completeness. Prerequisites: COS 226 and COS 240 or instructor's permission.

Reasoning with Data trains students to turn messy real-world datasets and experiments into credible empirical claims, covering data wrangling and visualization, core inference and causal tools (potential outcomes, DAGs, experiments, regression), and modern frontiers (LLMs, causal ML, benchmarks, and quasi-experiments). The course puts special emphasis on developing the practical skills that students will need in data-facing roles. Prerequisites: Basic Statistics: ORF 245 or equivalent -Introduction to ML: COS 324, ECE 435 or equivalent.

The principles underlying the generation and display of graphical pictures by computer. Hardware and software systems for graphics. Topics include: hidden surface and hidden line elimination, line drawing, shading, half-toning, user interfaces for graphical input, and graphic system organization. Two 90-minute lectures. Prerequisites: 217 and 226.

This course is an introduction to the concepts of 2D and 3D computer vision. It surveys a wide range of topics from level-level vision to high-level recognition. We will discuss concepts such as filtering and edge detection; cameras and shape reconstruction; segmentation and clustering; optical flow and tracking; object recognition; motion recognition; and statistical modeling of visual data. Throughout the course, there will also be an examination of aspects of human vision and perception that guide and inspire computer vision techniques. Prerequisites: COS 217, COS 226, and COS 324 (or equivalent).