Introduces the concepts and skills necessary to effectively use information technology. Includes basic concepts and some practical skills with computer and networks.

Exploration of topics in mathematics and engineering as they relate to classical architecture in Rome, Italy. In depth geometrical analysis and computer modeling of basic structures (arches, vaults, domes), and on-site studies of the Colosseum, Pantheon, Roman Forum, and St. Peter’s Basilica.

Companion course to CSE 4GS where theory is applied and lab experiments are carried out “in the field” in Rome, Italy. For final projects, students will select a complex structure (e.g., the Colosseum, the Pantheon, St. Peter’s, etc.) to analyze and model, in detail, using computer-based tools.

An introduction to computer science and programming using the Python language. The course will cover topics such as basic data types (e.g., integer, float, string), loops and iteration, basic data structures (e.g., list, set, dictionary), memory models, conditional statements, recursion, basic algorithm time complexity analysis, class design, and inheritance.

Introductory course for students interested in computer science and programming. Basics of programming including variables, conditionals, loops, functions/methods. Structured data storage such as arrays/lists and dictionaries, including data mutation. Hands-on experience with designing, writing, hand-tracing, compiling or interpreting, executing, testing, and debugging programs. Students solve relevant computational problems using a high-level programming language. CSE 8A is part of a two-course sequence (CSE 8A-B) that is equivalent to CSE 11. Students should take CSE 8B to complete the CSE 8A-B track. Students who have taken CSE 8B or CSE 11 may not take or receive credit for CSE 8A. Students may only receive credit for one of the following: BILD 62, COGS 18, CSE 8A, or CSE 6R. Recommended preparation: No prior programming experience is assumed, but comfort using computers is helpful. Students should consult the “CSE Course Placement Advice” web page for assistance in choosing which CSE course to take first.

This course allows students to use what they learned in introductory programming courses to make things happen in the real world. Working in teams, students will first learn to program Arduino-based devices.

Helps the Java programmer to be productive in the C++ programming environment. Topics include the similarities and differences between Java and C++ with special attention to pointers, operator overloading, templates, the STL, the preprocessor, and the C++ Runtime Environment.

A seminar providing an overview of a topic of current research interest to the instructor. The goal is to present a specialized topic in computer science and engineering students. May be taken for credit three times when topics vary.

A seminar format discussion led by CSE faculty on topics in central areas of computer science, concentrating on the relation among them, recent developments, and future directions.

Students assigned to tutor for a CSE course for the first time receive individual and group mentoring and training on how to be effective tutors to help them develop the skills and tools needed to be effective in their tutor role.

Independent reading or research by special arrangement with a faculty member.

Topics include an overview of various aspects of bioinformatics and will simultaneously introduce students to programming in Python. The assessments in the course represent various programming challenges and include solving diverse biological problems using popular bioinformatics tools.

Topics include an overview of various aspects of bioinformatics and will simultaneously introduce students to programming in Python. The assessments in the course represent various programming challenges and include solving diverse biological problems using popular bioinformatics tools. This will be a fully online class based on extensive educational materials and online educational platform Stepik developed with HHMI, NIH, and ILTI support.

Students learn the C programming language with an emphasis on high-performance numerical computation. The commonality across programming languages of control structures, data structures, and I/O is also covered. Techniques for using MATLAB to graph the results of C computations are developed.

Introduction to solution of engineering problems using computational methods. Formulating problem statements, selecting algorithms, writing computer programs, and analyzing output using MATLAB. Computational problems from nanoengineering, chemical engineering, and materials science are introduced. The course requires no prior programming skills.

This course examines the interrelationships of cognition and technology from the perspective of cognitive science. We address questions of importance for our increasingly technological society: How does technology shape our minds? How should what we know about our minds shape technology?

This class will teach fundamental Python programming skills and practices, including the “Zen of Python.” Students will focus on scientific computing and learn to write functions and tests, as well as how to debug code using the Jupyter Notebook programming environment.

Concepts of data and its role in science will be introduced, as well as the ideas behind data-mining, text-mining, machine learning, and graph theory, and how scientists and companies are leveraging those methods to uncover new insights into human cognition.

Application-oriented, hands-on introduction to engineering mathematics and design processes. Key mathematical concepts as they apply to engineering, including solving systems of equations and least-squares regression. In-class activities using Python and Arduino will complement the lectures and provide students hands-on experience with solving real-world engineering problems related to design, manufacturing and prototyping, electronics, and data analysis.

Engineer Your Success is designed to enhance your success as an engineering student (and later as an engineer) by developing key academic and personal skills. Learn how to study more effectively and uncover how to become the best engineer you can be. This course focuses on academic and personal planning, time management, study skills, and paths to personal growth. Activities include individual and collaborative exercises, personal reflections, and a final project.

Computer programming in MATLAB with elementary numerical analysis of engineering problems. Arithmetic and logical operations, arrays, graphical presentation of computations, symbolic mathematics, solutions of equations, and introduction to data structures.