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<!DOCTYPE html>
<html class="w-100 h-100">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>D-Lab Workshops</title>
<link rel="stylesheet" href="https://bootswatch.com/4/litera/bootstrap.min.css">
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script defer src="https://use.fontawesome.com/releases/v5.0.10/js/all.js"
integrity="sha384-slN8GvtUJGnv6ca26v8EzVaR9DC58QEwsIk9q1QXdCU8Yu8ck/tL/5szYlBbqmS+"
crossorigin="anonymous"></script>
<link rel="stylesheet" href="static/stylesheets/style.css">
</head>
<body class="w-100 h-100">
<!-- Navbar -->
<nav class="navbar navbar-expand-lg navbar-light bg-light fixed-top">
<a class="navbar-brand" href="index.html">D-Lab Workshops</a>
<button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarColor01"
aria-controls="navbarColor01" aria-expanded="false" aria-label="Toggle navigation">
<span class="navbar-toggler-icon"></span>
</button>
<div class="collapse navbar-collapse" id="navbarColor01">
<ul class="navbar-nav ml-auto">
<li class="nav-item">
<a class="nav-link active" href="python.html">Home</a>
</li>
<li class="nav-item">
<a class="nav-link" href="library.html">Library</a>
</li>
<li class="nav-item">
<a class="nav-link" target="_blank" href="https://dlab.berkeley.edu/">About D-Lab</a>
</li>
</ul>
</div>
</nav>
<!-- End of Navbar -->
<!-- Content -->
<div class="row mx-auto w-100 mt-5 justify-content-md-center">
<div class="col-md-offset-2 col-md-8 mt-5 text-center">
<h5 class="display-5">
All D-Lab Workshops
</h5>
<a href="https://dlab.berkeley.edu/training/upcoming-workshops"><button type="button" class="btn btn-info btn">Book a workshop!</button></a>
<p></p>
<!-- Workshops ordered alphabetically -->
<!-- Bash + Git -->
<blockquote class="display-5 clickable">Bash + Git</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Bash + Git</h4>
<p class="lead">Command line magic</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop will start by introducing you to navigating your computer’s file system and
basic Bash commands to remove the fear of working with the command line and to give you the
confidence to use it to increase your productivity. And then working with Git, a powerful
tool for keeping track of changes you make to the files in a project.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Bash-git">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FBash-Git&urlpath=lab%2Ftree%2FBash-Git%2F">
<i class="fas fa-database"></i> Datahub
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- Excel Data Analysis -->
<blockquote class="display-5 clickable">Excel Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Excel Fundamentals</h4>
<p class="lead">Working with Excel</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This is a three-hour introductory workshop that will provide an overview of Excel, with no prior experience assumed. Attendees will learn how to use functions for handling data and making calculations, how to build charts and pivot tables, and more.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Excel-fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://drive.google.com/drive/u/1/folders/1L5dgfjUZS-dLrFo2cwwbbbYSK_euCHar">
<i class="fas fa-database"></i> Workbook
</a>
<a class="btn btn-primary" tabindex="0" href="https://drive.google.com/drive/u/1/folders/1L5dgfjUZS-dLrFo2cwwbbbYSK_euCHar">
<i class="fas fa-book"></i> Google Sheets
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- Institutional Review Board (IRB) Fundamentals -->
<blockquote class="display-5 clickable">Institutional Review Board (IRB) Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Institutional Review Board (IRB) Fundamentals</h4>
<p class="lead">Get your IRB project approved</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
Are you starting a research project at UC Berkeley that involves human subjects? If so, one of the first steps you will need to take is getting IRB approval.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/IRB-fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://drive.google.com/drive/folders/1E0nqVOhIt8Ay0ncUSnvP5xPZiPsA8k9j?usp=sharing">
<i class="fas fa-database"></i> Workshop Materials
</a>
<a class="btn btn-primary" tabindex="0" href="https://docs.google.com/presentation/d/18YBUJo4T4e2ItvBniKeGmPAoFWZDrynay2WmUwXPBZ0/edit?usp=sharing">
<i class="fas fa-book"></i> Slides
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">MaxQDA Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">MaxQDA Fundamentals</h4>
<p class="lead">Using MaxQDA for data analysis</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This two-hour introductory workshop will teach you MaxQDA from scratch with clear introductions, concise examples, and support documents.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/maxqda-fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://docs.google.com/presentation/d/1rJ_5iOhRzBM5M-RqYoT3NojAhq-hUFwc/edit#slide=id.p1">
<i class="fas fa-book"></i> Slides
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Data Visualization</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Data Visualization</h4>
<p class="lead">Pandas, Matplotlib, and Seaborn</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
In this workshop, we provide an introduction to data visualization with Python. First, we'll cover some basics of visualization theory. Then, we'll explore how to plot data in Python using the matplotlib and seaborn packages.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Python-Data-Visualization">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Data-Visualization&urlpath=tree%2FPython-Data-Visualization%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Data-Visualization/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Data Wrangling</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Data Wrangling</h4>
<p class="lead">Manipulate DataFrames using Pandas in Python</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
In this workshop, we provide an introduction to data wrangling with Python. We will do so largely with the pandas package, which provides a rich set of tools to manipulate and interact with data frames, the most common data structure used when analyzing tabular data. We'll learn how to manipulate, index, merge, group, and plot data frames using pandas functions.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Python-data-wrangling">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Data-Wrangling-Pilot&urlpath=tree%2FPython-Data-Wrangling-Pilot%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Data-Wrangling-Pilot/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Deep Learning</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Deep Learning</h4>
<p class="lead">Create and train neural networks using Tensorflow and Keras</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop conveys the basics of deep learning in Python using keras on image datasets. Students are empowered with a general grasp of deep learning, example code that they can modify, a working computational environment, and resources for further study.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Python-Machine-Learning">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Deep-Learning&urlpath=tree%2FPython-Deep-Learning%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://colab.research.google.com/github/dlab-berkeley/Python-Deep-Learning/blob/main/lessons/01-Vanilla-Neural-Networks.ipynb">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Fundamentals</h4>
<p class="lead">The absolute basics</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience, with a focus on data science application. It covers the basics of Python and Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas. </p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Python-Fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="http://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Fundamentals&urlpath=lab%2Ftree%2FPython-Fundamentals%2F">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Fundamentals/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Geospatial Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Geospatial Fundamentals</h4>
<p class="lead">Analyzing geospatial data using GeoPandas in Python</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Python-Geospatial-Fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Geospatial-Fundamentals&urlpath=tree%2FPython-Geospatial-Fundamentals%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Geospatial-Fundamentals/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
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<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Intermediate</blockquote>
<!-- Featured Module Block -->
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<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Intermediate</h4>
<p class="lead">Building on the basics</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This three-part interactive workshop series is a follow-up to D-Lab's Python Fundamentals. It is intended for people who want to learn about core structures of Python that underpin data analysis. We cover loops and conditionals, creating your own functions, analysis and visualization in Pandas, and the workflow of a data science project.</p>
</div>
<!-- Link Column -->
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<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/python-intermediate">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Intermediate-Pilot&urlpath=lab%2Ftree%2FPython-Intermediate-Pilot%2F">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Intermediate-Pilot/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Machine Learning</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Machine Learning</h4>
<p class="lead">Classification, regression, clustering in Python</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
In this workshop, we provide an introduction to machine learning in Python. First, we'll cover some machine learning basics, including its foundational principles. Then, we'll dive into code, understanding how to perform regression, regularization, preprocessing, and classification.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Python-Machine-Learning">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Machine-Learning&urlpath=lab%2Ftree%2FPython-Machine-Learning%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Machine-Learning/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
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<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Text Analysis</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Text Analysis</h4>
<p class="lead">Bag-of-words, sentiment analysis, topic modeling, word embeddings, and more</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop is part of a loosely-coupled 4-part text analysis workshop series that will prepare participants to move forward with research that uses text analysis, with a special focus on social science applications. We explore fundamental approaches to applying computational methods to text in Python. We cover some of the major packages used in natural language processing, including scikit-learn, NLTK, spaCy, and Gensim.
</p>
</div>
<!-- Link Column -->
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<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/python-text-analysis">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Text-Analysis&urlpath=lab%2Ftree%2FPython-Text-Analysis%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Text-Analysis/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Web APIs</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Web APIs</h4>
<p class="lead">Obtain data from web platforms</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
In this workshop, we cover how to extract data from the web with APIs using Python. APIs are often official services offered by companies and other entities, which allow you to directly query their servers in order to retrieve their data. Platforms like The New York Times, Twitter and Reddit offer APIs to retrieve data.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Python-Web-APIs/">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Web-APIs&urlpath=lab%2Ftree%2FPython-Web-APIs%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Web-APIs/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Python Web Scraping</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Python Web Scraping</h4>
<p class="lead">Scrape HTML/CSS data from websites</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
In this workshop, we cover how to scrape data from the web using Python. Web scraping involves downloading a webpage's source code and sifting through the material to extract desired data.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Python-web-scraping">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FPython-Web-Scraping&urlpath=lab%2Ftree%2FPython-Web-Scraping%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/Python-Web-Scraping/HEAD">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">Qualtrics Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Qualtrics Fundamentals</h4>
<p class="lead">Data collection and survey design</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop will introduce Qualtrics with an orientation to the main interfaces for web survey design, sample management, corresponding with sample members, and exporting data.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Qualtrics-Fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://drive.google.com/drive/folders/1Q_t-U_S6tjUG6kgiAY7iGt9AsDt-9xUL?usp=sharing">
<i class="fas fa-book"></i> Slides
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">R Data Visualization</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">R Data Visualization</h4>
<p class="lead">Visualizing with R</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/R-Data-Visualization">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="http://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Data-Visualization&urlpath=rstudio%2F">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/R-Data-Visualization/HEAD?urlpath=rstudio">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">R Data Wrangling and Manipulation</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">R Data Wrangling and Manipulation</h4>
<p class="lead">Working with data</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop will introduce packages in R (notably dplyr and tidyr) that make data wrangling and manipulation much easier.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/R-Data-Wrangling">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Data-Wrangling&urlpath=rstudio%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">R Deep Learning</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">R Deep Learning</h4>
<p class="lead">Working with Keras in R</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
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. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels.
</p>
</div>
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<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/R-Deep-Learning">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Deep-Learning&urlpath=rstudio%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/R-Deep-Learning/HEAD?urlpath=rstudio">
<i class="fas fa-book"></i> Binder
</a>
<a class="btn btn-primary" tabindex="0" href="https://docs.google.com/presentation/d/1eQsjdzcareMpEK59EJS5gLqOWIcmQpTjDvQnXIBOh_c/edit?usp=sharing">
<i class="fas fa-book"></i> Slides
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- Data Manipulation in R -->
<blockquote class="display-5 clickable">R Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">R Fundamentals</h4>
<p class="lead">The absolute basics</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.
</p>
</div>
<!-- Link Column -->
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<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/R-Fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Fundamentals&urlpath=rstudio%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/R-Fundamentals/HEAD?urlpath=rstudio">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
<!-- BLOCK -->
<blockquote class="display-5 clickable">R Geospatial Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">R Geospatial Fundamentals</h4>
<p class="lead">Working with spatial data in R</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research.
</p>
</div>
<!-- Link Column -->
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<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/R-Geospatial-Fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="http://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Geospatial-Fundamentals&urlpath=rstudio%2F">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/R-Geospatial-Fundamentals/HEAD?urlpath=rstudio">
<i class="fas fa-book"></i> Binder
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
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<blockquote class="display-5 clickable">R Machine Learning with tidymodels</blockquote>
<!-- Featured Module Block -->
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<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">R Machine Learning with tidymodels</h4>
<p class="lead">Using R for ML</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop offers an introduction to machine learning algorithms by making use of the tidymodels package.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/R-Machine-Learning">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2FR-Machine-Learning&urlpath=rstudio%2F&branch=main">
<i class="fas fa-database"></i> Datahub
</a>
<a class="btn btn-primary" tabindex="0" href="https://mybinder.org/v2/gh/dlab-berkeley/R-Machine-Learning/HEAD?urlpath=rstudio">
<i class="fas fa-book"></i> Binder
</a>
<a class="btn btn-primary" tabindex="0" href="https://docs.google.com/presentation/d/1eQsjdzcareMpEK59EJS5gLqOWIcmQpTjDvQnXIBOh_c/edit?usp=sharing">
<i class="fas fa-book"></i> Slides
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
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<blockquote class="display-5 clickable">R Text Analysis</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">R Text Analysis</h4>
<p class="lead">Preprocessing, topic modeling, word embeddings and more</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
In this workshop, we'll focus fundamental approaches to applying computational and data visualization methods to text in R. We'll cover a "tidy data" approach to natural language processing, which incorporates tidyverse data transformations,tidytext, tidymodels and a host of other text related packages.
</p>
</div>
<!-- Link Column -->
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<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/R-text-analysis">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="http://dlab.datahub.berkeley.edu/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fdlab-berkeley%2Fr-text-analysis&urlpath=rstudio%2F">
<i class="fas fa-database"></i> Datahub
</a>
</div>
</div>
</div>
</div>
<!-- Stata Fundamentals -->
<blockquote class="display-5 clickable">Stata Fundamentals</blockquote>
<!-- Featured Module Block -->
<div class="card border-info content">
<div class="row card-body">
<!-- Title Column -->
<div class="d-flex justify-content-center flex-column col-md-3">
<h4 class="card-title">Stata Fundamentals</h4>
<p class="lead">The basics of Stata</p>
</div>
<!-- Paragraph Column -->
<div class="d-flex justify-content-center flex-column col-md-6">
<p class="card-text">
This workshop is a three-part introductory series that will teach you Stata from scratch with clear introductions, concise examples, and support documents.
</p>
</div>
<!-- Link Column -->
<div class="d-flex justify-content-center pb-4 flex-column col-md-3">
<div class="btn-group-vertical my-3">
<a class="btn btn-primary" tabindex="0" href="https://github.com/dlab-berkeley/Stata-Fundamentals">
<i class="fab fa-github"></i> Github
</a>
<a class="btn btn-primary" tabindex="0" href="https://docs.google.com/presentation/d/1UsaH3xREfqFM-tW0FQ4Uykfwnfv8CccLSIsLZH_bDG0/edit?usp=sharing">
<i class="fas fa-book"></i> Slides
</a>
</div>
</div>
</div>
</div>
<!-- End of Featured Module Block -->
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