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101 - 110 of 151 results for: all courses

GEOPHYS 141: Remote Sensing of the Oceans (EARTHSYS 141, EARTHSYS 241, ESS 141, ESS 241)

How to observe and interpret physical and biological changes in the oceans using satellite technologies. Topics: principles of satellite remote sensing, classes of satellite remote sensors, converting radiometric data into biological and physical quantities, sensor calibration and validation, interpreting large-scale oceanographic features.
Terms: Win | Units: 3-4 | UG Reqs: GER: DB-NatSci, WAY-AQR | Grading: Letter or Credit/No Credit
Instructors: Arrigo, K. (PI)

GEOPHYS 160: D^3: Disasters, Decisions, Development

This class connects the science behind natural disasters with the real-world constraints of disaster management and development. In each iteration of this class we will focus on a specific, disaster-prone location as case study. By collaborating with local stakeholders we will explore how science and engineering can make a make a difference in reducing disaster risk in the future. Offered every other year.
Terms: not given this year, last offered Winter 2016 | Units: 3-5 | UG Reqs: WAY-AQR, WAY-SMA | Grading: Letter (ABCD/NP)

HUMBIO 51: Big Data for Biologists - Decoding Genomic Function

Biology and medicine are becoming increasingly data-intensive fields. This course is designed to introduce students interested in human biology and related fields to methods for working with large biological datasets. There will be in-class activities analyzing real data that have revealed insights about the role of the genome and epigenome in health and disease. For example, we will explore data from large-scale gene expression and chromatin state studies. The course will provide an introduction to the relevant topics in biology and to fundamental computational skills such as editing text files, formatting and storing data, visualizing data and writing data analysis scripts. Students will become familiar with both UNIX and Python. This course is designed at the introductory level. Previous university-level courses in biology and programming experience are not required.
Terms: Aut | Units: 3 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit

HUMBIO 88: Introduction to Statistics for the Health Sciences

Students will learn the statistical tools used to describe and analyze data in the fields of medicine and epidemiology. This very applied course will rely on current research questions and publicly available data. Students will gain proficiency with Stata to do basic analyses of health-related data, including linear and logistic regression, and will become sophisticated consumers of health-related statistical results.
Terms: Win | Units: 4 | UG Reqs: GER:DB-Math, WAY-AQR | Grading: Letter (ABCD/NP)
Instructors: Kurina, L. (PI)

HUMBIO 89: Introduction to Health Sciences Statistics

This course aims to provide a firm grounding in the foundations of probability and statistics, with a focus on analyzing data from the health sciences. Students will learn how to read, interpret, and critically evaluate the statistics in medical and biological studies. The course also prepares students to be able to analyze their own data, guiding them on how to choose the correct statistical test, avoid common statistical pitfalls, and perform basic functions in R deducer. Cardinal Course certified by the Haas Center.
Terms: Aut, Win | Units: 3 | UG Reqs: GER:DB-Math, WAY-AQR | Grading: Letter or Credit/No Credit

HUMBIO 154B: Principles of Epidemiology

Epidemiology is the study of the distribution and determinants of health and disease in human populations. In this course, students will learn about design, measures of disease occurrence and measures of association between exposures - be they environmental, behavioral or genetic - and health outcomes of interest. Students will also learn about how error, confounding and bias can impact epidemiological results. The course draws on both classic and contemporary research articles, which students will learn to critically appraise. Through lectures, problem sets, written responses to original articles and in-class discussions, students will gain a solid foundation in epidemiology. Upper division course with preference given to upperclassmen.
Terms: Aut | Units: 3 | UG Reqs: WAY-AQR | Grading: Letter (ABCD/NP)
Instructors: Kurina, L. (PI)

HUMBIO 154C: Cancer Epidemiology

Clinical epidemiological methods relevant to human research in cancer will be the focus. The concepts of risk; case control, cohort, and cross-sectional studies; clinical trials; bias; confounding; interaction; screening; and causal inference will be introduced and applied. Social, political, economic, and ethical controversies surrounding cancer screening, prevention, and research will be considered. Human Biology 154 courses can be taken separately or as a series. Prerequisite: Human Biology core or Biology Foundations or equivalent, or instructor consent.
Terms: Win | Units: 4 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit
Instructors: Fisher, P. (PI)

LINGUIST 180: From Languages to Information (CS 124, LINGUIST 280)

Extracting meaning, information, and structure from human language text, speech, web pages, social networks. Introducing methods (string algorithms, edit distance, language modeling, machine learning classifiers, neural embeddings, inverted indices, collaborative filtering, PageRank), applications (chatbots, sentiment analysis, information retrieval, question answering, text classification, social networks, recommender systems), and ethical issues in both. Prerequisites: CS103, CS107, CS109.
Terms: Win | Units: 3-4 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit

MATSCI 158: Soft Matter in Biomedical Devices, Microelectronics, and Everyday Life (BIOE 158)

The relationships between molecular structure, morphology, and the unique physical, chemical, and mechanical behavior of polymers and other types of soft matter are discussed. Topics include methods for preparing synthetic polymers and examination of how enthalpy and entropy determine conformation, solubility, mechanical behavior, microphase separation, crystallinity, glass transitions, elasticity, and linear viscoelasticity. Case studies covering polymers in biomedical devices and microelectronics will be covered. Recommended: ENGR 50 and Chem 31A or equivalent.
Terms: Win | Units: 4 | UG Reqs: WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit
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