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11 - 20 of 25 results for: CS106A

CS 106AP: Programming Methodology in Python

Introduction to the engineering of computer applications in Python, emphasizing modern software engineering principles: decomposition, abstraction, testing and good programming style. This course covers most of the same material as the other versions of CS106A, but using the Python programming language which is popular for general engineering and web development. Required readings will all be available for free on the web. Students are encouraged to bring a laptop to lecture to do the live exercises which are integrated with lecture. No prior programming experience required. To enroll in this class, enroll in CS 106A Section 3. Satisfies WAY-FR requirement.
Terms: Win, Spr, Sum | Units: 3-5 | Grading: Letter or Credit/No Credit

CS 106E: Practical Exploration of Computing

A follow up class to CS106A for non-majors which will both provide practical web programming skills and cover essential computing topics including computer security and privacy. Additional topics will include digital representation of images and music, an exploration of how the Internet works, and a look at the internals of the computer. Students taking the course for 4 units will be required to carry out supplementary programming assignments in addition to the course's regular assignments. Prerequisite: 106A or equivalent
Terms: Spr | Units: 3-4 | Grading: Letter or Credit/No Credit

CS 193C: Client-Side Internet Technologies

Client-side technologies used to create web sites such as Google maps or Gmail. Includes HTML5, CSS, JavaScript, the Document Object Model (DOM), and Ajax. Prerequisite: programming experience at the level of CS106A.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Young, P. (PI)

CS 253: Building for Digital Health (MED 253)

This project-based course will provide a comprehensive overview of key requirements in the design and full-stack implementation of a digital health research application. Several pre-vetted and approved projects from the Stanford School of Medicine will be available for students to select from and build. Student teams will learn about all necessary approval processes to deploy a digital health solution (data privacy clearance/I RB approval, etc.) and be guided in the development of front-end and back-end infrastructure using best practices. The final project will be the presentation and deployment of a fully approved digital health research application. CS106A/B, Recommended: CS193P/A, CS142, CS47, CS110.
Terms: Aut | Units: 3 | Grading: Medical Option (Med-Ltr-CR/NC)

CS 270: Modeling Biomedical Systems: Ontology, Terminology, Problem Solving (BIOMEDIN 210)

Methods for modeling biomedical systems and for building model-based software systems. Emphasis is on intelligent systems for decision support and Semantic Web applications. Topics: knowledge representation, controlled terminologies, ontologies, reusable problem solvers, and knowledge acquisition. Students learn about current trends in the development of advanced biomedical software systems and acquire hands-on experience with several systems and tools. Prerequisites: CS106A, basic familiarity with biology, probability, and logic.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit

CS 377N: Introduction to the Design of Smart Products (ME 216M)

This course will focus on the technical mechatronic skills as well as the human factors and interaction design considerations required for the design of smart products and devices. Students will learn techniques for rapid prototyping of smart devices, best practices for physical interaction design, fundamentals of affordances and signifiers, and interaction across networked devices. Students will be introduced to design guidelines for integrating electrical components such as PCBs into mechanical assemblies and consider the physical form of devices, not just as enclosures but also as a central component of the smart product. Prerequisites include: CS106A and E40 highly recommended, or instructor approval.
Terms: Spr | Units: 3-4 | Grading: Letter or Credit/No Credit

CS 448M: Making Making Machines for Makers

An introductory, project-based exploration of systems and processes for making things using computer-aided design and manufacturing, and an introduction to machines and machine tools. Emphasis will be placed on building novel machines and related software for use by "makers" and interactive machines. Course projects will encourage students to understand, build and modify/hack a sequence of machines: (1) an embroidery machine for custom textiles, (2) a paper cutting machine (with drag knife) for ornamental design, and (3) an XY plotter with Arduino controller. Through these projects students explore both (i) principles of operation (mechanical, stepper motors and servos, electrical control, computer software), and (ii) computer algorithms (trajectory, tool path, design). Current trends in interactive machines will be surveyed. The course will culminate in a final student-selected project. Prerequisite: CS106A or equivalent programming experience. Students should have a desire to make things.
Terms: Spr | Units: 3-4 | Grading: Letter or Credit/No Credit

EE 104: Introduction to Machine Learning

Introduction to machine learning. Formulation of supervised and unsupervised learning problems. Regression and classification. Data standardization and feature engineering. Loss function selection and its effect on learning. Regularization and its role in controlling complexity. Validation and overfitting. Robustness to outliers. Simple numerical implementation. Experiments on data from a wide variety of engineering and other disciplines. Undergraduate students should enroll for 5 units, and graduate students should enroll for 3 units. Prerequisites: EE 103; EE 178 or CS 109; CS106A or equivalent.
Terms: Spr | Units: 3-5 | Grading: Letter or Credit/No Credit

ENGR 70A: Programming Methodology (CS 106A)

Introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Emphasis is on good programming style and the built-in facilities of respective languages. No prior programming experience required. Alternative versions of CS106A may be available which cover most of the same material but in different programming languages.
Terms: Aut, Win, Spr, Sum | Units: 3-5 | UG Reqs: GER:DB-EngrAppSci, WAY-FR | Grading: Letter or Credit/No Credit

IMMUNOL 207: Essential Methods in Computational and Systems Immunology

Introduction to the major underpinnings of systems immunology: first principles of development of computational approaches to immunological questions and research; details of the algorithms and statistical principles underlying commonly used tools; aspects of study design and analysis of data sets. Prerequisites: CS106a and CS161 strongly recommended.
Terms: Spr | Units: 3 | Grading: Medical Option (Med-Ltr-CR/NC)
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