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11 - 20 of 100 results for: CS

CS 104: Introduction to Essential Software Systems and Tools

Concepts that are prerequisites to many different CS classes, such as version control, debugging, and basic cryptography and networking, are either left for students to figure out on their own or are taught in "crash course" form on-the-fly during other, unrelated classes. We propose to develop a course that will teach students the skills necessary to be successful computer scientists, such as the command line, source code management and debugging, security and cryptography, containers and virtual machines, and cloud computing. In this course, students will both become proficient with practical tools and develop a deeper, intuitive understanding of the involved software systems and computer science concepts. With this deeper understanding, students can leverage critical thinking skills to intelligently and efficiently configure and troubleshoot software systems, assess the security and efficiency of particular tool usages, and synthesize new automation pipelines that integrate multiple more »
Concepts that are prerequisites to many different CS classes, such as version control, debugging, and basic cryptography and networking, are either left for students to figure out on their own or are taught in "crash course" form on-the-fly during other, unrelated classes. We propose to develop a course that will teach students the skills necessary to be successful computer scientists, such as the command line, source code management and debugging, security and cryptography, containers and virtual machines, and cloud computing. In this course, students will both become proficient with practical tools and develop a deeper, intuitive understanding of the involved software systems and computer science concepts. With this deeper understanding, students can leverage critical thinking skills to intelligently and efficiently configure and troubleshoot software systems, assess the security and efficiency of particular tool usages, and synthesize new automation pipelines that integrate multiple tools. To summarize, instead of having just a cursory understanding of how to use these tools, students will learn how to most effectively use these tools to become proficient programmers and computer scientists. In addition, this course can provide a gentle introduction to potentially challenging computer science concepts (e.g., networking) that become a focus in subsequent courses and also help motivate some of the tool usages they will see later in the degree program.
Terms: Win | Units: 3

CS 106A: Programming Methodology

Introduction to the engineering of computer applications emphasizing modern software engineering principles: program design, decomposition, encapsulation, abstraction, and testing. Emphasis is on good programming style and the built-in facilities of respective languages. Uses the Python programming language. No prior programming experience required.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: WAY-FR, GER:DB-EngrAppSci

CS 106B: Programming Abstractions

Abstraction and its relation to programming. Software engineering principles of data abstraction and modularity. Object-oriented programming, fundamental data structures (such as stacks, queues, sets) and data-directed design. Recursion and recursive data structures (linked lists, trees, graphs). Introduction to time and space complexity analysis. Uses the programming language C++ covering its basic facilities. Prerequisite: 106A or equivalent.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: GER:DB-EngrAppSci, WAY-FR

CS 106L: Standard C++ Programming Laboratory

This class explores features of the C++ programming language beyond what's covered in CS106B. Topics include core C++ language features (e.g. const-correctness, operator overloading, templates, move semantics, and lambda expressions) and standard libraries (e.g. containers, algorithms, and smart pointers). Pre- or corequisite: CS106B or equivalent. Prerequisite: CS106B or equivalent. CS106L may be taken concurrently with CS106B.
Terms: Aut, Win, Spr | Units: 1
Instructors: Whitney, H. (PI)

CS 107: Computer Organization and Systems

Introduction to the fundamental concepts of computer systems. Explores how computer systems execute programs and manipulate data, working from the C programming language down to the microprocessor. Topics covered include: the C programming language, data representation, machine-level code, computer arithmetic, elements of code compilation, memory organization and management, and performance evaluation and optimization. Prerequisites: 106B or X, or consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: WAY-FR, GER:DB-EngrAppSci

CS 107ACE: Problem-solving Lab for CS107

Additional problem solving practice for the introductory CS course CS107. Sections are designed to allow students to acquire a deeper understanding of CS and its applications, work collaboratively, and develop a mastery of the material. Limited enrollment, permission of instructor required. Concurrent enrollment in CS 107 required.
Terms: Aut, Win, Spr | Units: 1

CS 107E: Computer Systems from the Ground Up

Introduction to the fundamental concepts of computer systems through bare metal programming on the Raspberry Pi. Explores how five concepts come together in computer systems: hardware, architecture, assembly code, the C language, and software development tools. Students do all programming with a Raspberry Pi kit and several add-ons (LEDs, buttons). Topics covered include: the C programming language, data representation, machine-level code, computer arithmetic, compilation, memory organization and management, debugging, hardware, and I/O. Enrollment limited to 40. Check website for details: http://cs107e.stanford.edu on student selection process. Prerequisite: CS106B or CS106X, and consent of instructor. There is a $75 course lab fee.
Terms: Win, Spr | Units: 3-5 | UG Reqs: WAY-FR

CS 108: Object-Oriented Systems Design

Software design and construction in the context of large OOP libraries. Taught in Java. Topics: OOP design, design patterns, testing, graphical user interface (GUI) OOP libraries, software engineering strategies, approaches to programming in teams. Prerequisite: 107.
Terms: Win | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci

CS 109: Introduction to Probability for Computer Scientists

Topics include: counting and combinatorics, random variables, conditional probability, independence, distributions, expectation, point estimation, and limit theorems. Applications of probability in computer science including machine learning and the use of probability in the analysis of algorithms. Prerequisites: 103, 106B or X, multivariate calculus at the level of MATH 51 or CME 100 or equivalent.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: WAY-AQR, WAY-FR, GER:DB-EngrAppSci

CS 109ACE: Problem-solving Lab for CS109

Additional problem solving practice for the introductory CS course CS109. Sections are designed to allow students to acquire a deeper understanding of CS and its applications, work collaboratively, and develop a mastery of the material. Enrollment limited to 30 students, permission of instructor required. Concurrent enrollment in CS 109 required.
Terms: Aut, Win, Spr | Units: 1
Instructors: Qin, M. (PI)
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