Bash + Git

Command line magic

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.

Excel Fundamentals

Working with Excel

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.

Institutional Review Board (IRB) Fundamentals

Get your IRB project approved

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.

MaxQDA Fundamentals

Using MaxQDA for data analysis

This two-hour introductory workshop will teach you MaxQDA from scratch with clear introductions, concise examples, and support documents.

Python Data Visualization

Pandas, Matplotlib, and Seaborn

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.

Python Data Wrangling

Manipulate DataFrames using Pandas in Python

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.

Python Deep Learning

Create and train neural networks using Tensorflow and Keras

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.

Python Fundamentals

The absolute basics

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.

Python Geospatial Fundamentals

Analyzing geospatial data using GeoPandas in Python

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.

Python Intermediate

Building on the basics

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.

Python Machine Learning

Classification, regression, clustering in Python

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.

Python Text Analysis

Bag-of-words, sentiment analysis, topic modeling, word embeddings, and more

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.

Python Web APIs

Obtain data from web platforms

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.

Python Web Scraping

Scrape HTML/CSS data from websites

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.

Qualtrics Fundamentals

Data collection and survey design

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.

R Data Visualization

Visualizing with R

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.

R Data Wrangling and Manipulation

Working with data

This workshop will introduce packages in R (notably dplyr and tidyr) that make data wrangling and manipulation much easier.

R Deep Learning

Working with Keras 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. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels.

R Fundamentals

The absolute basics

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.

R Geospatial Fundamentals

Working with spatial data in R

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.

R Machine Learning with tidymodels

Using R for ML

This workshop offers an introduction to machine learning algorithms by making use of the tidymodels package.

R Text Analysis

Preprocessing, topic modeling, word embeddings and more

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.

Stata Fundamentals

The basics of Stata

This workshop is a three-part introductory series that will teach you Stata from scratch with clear introductions, concise examples, and support documents.