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 largescale oceanographic features.
Terms: Win

Units: 34

UG Reqs: GER: DBNatSci, WAYAQR

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 realworld constraints of disaster management and development. In each iteration of this class we will focus on a specific, disasterprone 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: 35

UG Reqs: WAYAQR, WAYSMA

Grading: Letter (ABCD/NP)
HUMBIO 51: Big Data for Biologists  Decoding Genomic Function
Biology and medicine are becoming increasingly dataintensive 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 inclass 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 largescale 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 universitylevel courses in biology and programming experience are not required.
Terms: Aut

Units: 3

UG Reqs: WAYAQR

Grading: Letter or Credit/No Credit
Instructors:
Kundaje, A. (PI)
;
Salmeen, A. (PI)
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 healthrelated data, including linear and logistic regression, and will become sophisticated consumers of healthrelated statistical results.
Terms: Win

Units: 4

UG Reqs: GER:DBMath, WAYAQR

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:DBMath, WAYAQR

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 inclass discussions, students will gain a solid foundation in epidemiology. Upper division course with preference given to upperclassmen.
Terms: Aut

Units: 3

UG Reqs: WAYAQR

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 crosssectional 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: WAYAQR

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: 34

UG Reqs: WAYAQR

Grading: Letter or Credit/No Credit
Instructors:
Jurafsky, D. (PI)
;
Chen, J. (TA)
;
CruzAlbrecht, L. (TA)
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more instructors for LINGUIST 180 »
Instructors:
Jurafsky, D. (PI)
;
Chen, J. (TA)
;
CruzAlbrecht, L. (TA)
;
Kabaghe, C. (TA)
;
Khandelwal, U. (TA)
;
Mendelsohn, J. (TA)
;
Mistele, M. (TA)
;
Pattabi, V. (TA)
;
Plattner, C. (TA)
;
Quinn, M. (TA)
;
Redmond, S. (TA)
MATH 114: Introduction to Scientific Computing (CME 108)
Introduction to Scientific Computing Numerical computation for mathematical, computational, physical sciences and engineering: error analysis, floatingpoint arithmetic, nonlinear equations, numerical solution of systems of algebraic equations, banded matrices, least squares, unconstrained optimization, polynomial interpolation, numerical differentiation and integration, numerical solution of ordinary differential equations, truncation error, numerical stability for time dependent problems and stiffness. Implementation of numerical methods in MATLAB programming assignments. Prerequisites:
MATH 51, 52, 53; prior programming experience (MATLAB or other language at level of
CS 106A or higher).
Terms: not given this year, last offered Summer 2019

Units: 3

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYFR

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: WAYAQR, WAYSMA

Grading: Letter or Credit/No Credit
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