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Geospatial Data in Python with GeoPandas

Geospatial data are an important component of social science and humanities data visualization and analysis. This workshop will introduce basic methods for working with geospatial data in Python using GeoPandas, a relatively new Python library for working with geospatial data that has matured and stabilized in the last few years. In the workshop we will import geospatial data stored in shapefiles and CSV files into geopandas objects. We will explore methods for subsetting and spatial reshaping these objects.

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Geospatial Data in R, Part 3: Raster Data

Raster data are used to represent geographic phenomena that are present and can be measured anywhere in a study area, like elevation, temperature, rainfall, land cover, soil type, etc. These data are a valuable resource for social scientists, planners, and engineers as well as natural scientists. This workshop will introduce basic raster concepts and methods for working with raster data in R. Participants will learn how to import and store raster data as spatial objects. We will explore methods for plotting rasters and manipulating raster data values.

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Introduction to Crowdsourcing in Research: A discussion with Kate Beck on benefits and concerns

Crowdsourcing is a method increasingly used in qualitative, quantitative, and mixed-methods research. However, many researchers remain unclear about what this method is, when it may be appropriate to use, and how it could be implemented. Please join Kate Beck, Program Lead at UC Berkeley's Safe Transportation Research and Education Center (SafeTREC), to learn more about this research method. 

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ArcGIS Online - a Geospatial Data, Mapping, Spatial Analysis and Web Publishing Platform

Posted: Nov, 06, 2018

By: Patty Frontiera

Looking for a tool to create a map? Share geographic data online? Develop a map-based website? Perform spatial analysis? Geocode addresses? If so, give ArcGIS Online a try. 
 
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Introduction to Artificial Neural Networks

This workshop introduces Artificial Neural Networks (ANNs), a group of popular machine learning algorithms. No prior knowledge is required, though previous experience with other machine learning algorithms would be helpful. The workshop will be divided into three parts:

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Google Collaboratory as a Data Science Learning Environment

Posted: Oct, 30, 2018

By: Patty Frontiera

As a D-Lab instructor, I have designed and taught many workshops on the use of geospatial tools and techniques using both ArcGIS and QGIS software as well R and Python programming environments. Software installation is often a pain point for students and can dissuade new learners from moving forward.

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Intro to Deep Learning in R

This workshop introduces the basic concepts of Deep Learning - the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data.

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The available spaces and the waitlist for this event are both full.

Python Fundamentals: Part 4

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 4 Topics: We will applying the skills learned during previous sessions to a real world social science example.

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The available spaces and the waitlist for this event are both full.

Python Fundamentals: Part 3

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 3 Topics:

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The available spaces and the waitlist for this event are both full.

Python Fundamentals: Part 2

Part 2 Topics:

  • Lists
  • Loops
  • Conditionals
  • Functions
  • Scope

Knowledge requirements: Python Fundamentals: Part 1 or equivalent prior knowledge

Registration note: To participate in multiple parts of this series, please be sure to register for each day separately.

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The available spaces and the waitlist for this event are both full.

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