2013-2014 2014-2015 2015-2016 2016-2017 2017-2018
Browse
by subject...
    Schedule
view...
 

11 - 20 of 20 results for: CS106A

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 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.
Terms: Win | Units: 3 | 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. In this initial offering, enrollment is limited to 50 students. 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. Summer quarter enrollment is limited. Alternative versions of CS106A are available which cover most of the same material but in different programming languages: Java [Fall, Win, Spr, or Sum qtr enroll in CS106A Section 1] Javascript [Fall qtr enroll in CS 106A Section 2] Python [Winter or Spring qtr enroll in CS 106A Section 3]
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)

ME 47: Press Play: Interactive Device Design

This course provides an introduction to the human-centered and technical workings behind interactive devices ranging from cell phones and video controllers to household appliances and smart cars. This is a hands-on, lab-based course; there will be no midterm or final. Course topics include electronics prototyping, interface prototyping, sensors and actuators, microcontroller development, physical prototyping and user testing. For the final project, students will build a working MP3 player prototype of their own design, using embedded microcontrollers, digital audio decoders, component sensors and other electronic hardware. Prior experience in programming, such as CS106A (or equivalent) or electronics, such as ENG40A (or equivalent) preferred. Students must attend the first class.
Terms: not given this year | Units: 4-5 | Grading: Letter or Credit/No Credit

ME 52SI: Scan, Model, Print! Designing with 3D Technology

Think 3D scanning, modeling, and printing technology is just about plastic widgets? Think again! Immerse yourself in a world of custom prosthetics, manufacturing in space, autonomous cars, and much more. This hands-on engineering design course teaches advanced 3D imaging and computational modeling skills in order to leverage the unique benefits of additive manufacturing to solve complex problems. Students will connect the theory behind these tools to direct experience with the equipment and software. Short assignments at the start of the quarter will build students' core competencies and prepare them for a team-based, open-ended project. Class time will be a mixture of lecture, lab, guest speakers, and field trips. Recommended: basic CAD, fabrication, and programming experience (e.g. ME103D, 203, CS106A or equivalents).
Terms: not given this year, last offered Spring 2015 | Units: 2 | Grading: Satisfactory/No Credit

ME 216M: Introduction to the Design of Smart Products

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, E40, and ME 210 or ME218 highly recommended, or instructor approval.
Terms: Spr | Units: 4 | Grading: Letter or Credit/No Credit

PHYSICS 91SI: Practical Computing for Scientists

Essential computing skills for researchers in the natural sciences. Helping students transition their computing skills from a classroom to a research environment. Topics include the Unix operating system, the Python programming language, and essential tools for data analysis, simulation, and optimization. More advanced topics as time allows. Prerequisite: CS106A or equivalent.
Terms: Spr | Units: 2 | Grading: Satisfactory/No Credit

SOMGEN 217SI: Fundamentals of Digital Health Innovation

Digital Health is an emerging field that sits at the intersection of healthcare and technology. Last year, healthcare spending in the United States surpassed $3.2T, and remains an unmet need. To fully address this issue, this requires expertise in healthcare and technology trends. This class will focus on how understanding healthcare trends of the past, present and future combined with the innovative technology trends can ultimately be utilized to drive innovation in healthcare. Some topics covered will revolve around technology trends in healthcare and healthcare stakeholders, such as providers, payers, biotechnology and pharmaceutical companies, FDA, and the financial markets. Prerequisities for the course are BIO41 or CS106A or equivalent.
Terms: not given this year, last offered Spring 2017 | Units: 1 | Grading: Medical Satisfactory/No Credit
Filter Results:
term offered
updating results...
number of units
updating results...
time offered
updating results...
days
updating results...
UG Requirements (GERs)
updating results...
component
updating results...
career
updating results...
© Stanford University | Terms of Use | Copyright Complaints