Log in

Sign up for our weekly newsletter!

Introduction to Bash + Git

Introduction to Bash + Git

Installation Instructions

Overview

An introduction to programming basics in Bash and GitHub that are often assumed, but that you might have never had good instruction on!

Log in to register for this training.

Python Text Analysis Fundamentals: Parts 1-3

Overview

This workshop is one of a three-part series that will prepare participants to move forward with text analysis research, with a special focus on humanities and social science applications.

  • Part 1: Basic Tools and Techniques

  • Part 2: Unsupervised Approaches


  • Part 3: Supervised Methods


Log in to register for this training.

R Fundamentals: Parts 1-4

Overview

Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills for free at our R workshops!

Log in to register for this training.
Projects as a Learning Tool

Posted: Apr, 06, 2021

By: Emily Grabowski

Let’s say you’re new to programming, or maybe you’ve coded before but you’re tackling a new concept. You’ve read a blog post or taken a workshop, and have a general sense of what is going on. But how do you take this to the next level? One of my favorite ways to dive into a new technique is to simply try it out.

Read →

Stata Fundamentals: Parts 1-3

Overview

This three-part series will cover the following materials:

Part 1:  Introduction

Log in to register for this training.
Visuals for Everyone: An Exercise On The Importance of Intuitive Data Visualization

Posted: Mar, 30, 2021

By: Daphne Yang

A couple years ago, I took an undergraduate biostatistics course here at UC Berkeley and vividly remember one of the first discussion section activities on interpreting data and visualizations. From this activity, I learned about why, as data consumers, we must always be aware of not only what visualizations are really representing but also understanding where the data is really coming from. While this might seem obvious, this has been one of the most valuable lessons as an aspiring data scientist/enthusiast.

Read →

Pages