|Title||Course number||Days and Times||Description||Instructor||Units|
|Foundations of Data Science||CS/ INFO/ STAT C8||MWF 11-12||
Designed for students from any major, Data 8 is an innovative introduction to core concepts of computer programming and statistics. Get hands-on experience working with data while exploring real-world issues ranging from racial profiling to social networks to California water usage.
|Time Series Analysis: Sea Level Rise and Coastal Flooding||CIV ENG 88B||Tu 12-2||
In this course, we will pursue analysis of long-term records of coastal water levels in the context of sea level rise. We will cover the collection, evaluation, visualization and analysis of time series data using long-term records of sea levels from coastal sites around the world.
|Data Science and the Mind||COGSCI 88||Mon 12-2||
How does the human mind work? We explore this question by analyzing a range of data concerning such topics as human rationality and irrationality, human memory, how objects and events are represented in the mind, and the relation of language and cognition.
|Exploring Geospatial Data||ESPM 88-A||Tue 3-5||
From interactive web maps to spatial data analysis, digital geographic data and information are becoming an important part of the data science landscape. Almost everything happens somewhere that can be mapped on the surface of the earth.
|Data Science Applications in Geography||GEOG 88||MW 5-7||
Data science methods are increasingly important in geography and earth science. This course introduces some of the particular challenges of working with spatial data arising from characteristics specific to such data.
|How Does History Count? Exploring Japanese-American Internment through Digital Sources||Hist 88||Tue 2-4||
On February 19, 1942, Executive Order 9066 authorized the detention of more than 120,000 people of Japanese descent, most of them American citizens living on the west coast.
|Data and Ethics||INFO 88||Mon 10-12||
This course provides an introduction to critical and ethical issues surrounding data and society.
|Data Science for Cognitive Neuroscience||L&S 88-5||Tue 1-3||
The human brain is a complex information processing system and is currently the topic of multiple fascinating branches of research. Understanding how it works is a very challenging scientific task.
|Leila Wehbe, Fatma Imamoglu, Mark Lescroart||2|
|Crime and Punishment: Taking the Measure of the US Justice System||Legal Studies 88||Tu 8-10||
We will explore how data are used in the criminal justice system by exploring the debates surrounding mass incarceration and evaluating a number of different data sources that bear on police practices, incarceration, and criminal justice reform.
|Immunotherapy of Cancer: Success and Failure||MCB 88||Mon 2-4||
We will work with a variety of datasets that describe a molecular view of cells and how they divide. We will learn about the processes that cause cells to become specialized (differentiate) and to give rise to cancer (transform).
|Probability and Mathematical Statistics in Data Science||STAT 88||
In this connector course we will state precisely and prove results discovered in the foundational data science course through working with data.
|Introduction to Matrices and Graphs in Data Science||STAT 89A||Mon 1-3pm||
This connector will cover introductory topics in the mathematics of data science, focusing on discrete probability and linear algebra and the connections between them that are useful in modern theory and practice.
|Principles and Techniques of Data Science||CS C100 / Stat C100||Tu Th||
Combining data, computation, and inferential thinking, data science is redefining how people and organizations solve challenging problems and understand the world.
|Bin Yu, Deborah Nolan, Joseph Gonzalez, Joseph Hellerstein||4|
|Probability for Data Science||Stat 140||TuTh 3:30-5:00||
This new course introduces students to probability theory using both mathematics and computation, the two main tools of the subject.
|Statistical Methods for Data Science||Stat 28||MWF 11-12||
Stat 28 is a new course for students in many disciplines who have taken Data 8 and want to learn more advanced techniques without the additional mathematics called on in upper-division statistics. Topics include group comparisons and ANOVA, standard parametric statistical models, multivariate data visualization, multiple linear regression and classification, classification and regression trees and random forests.