Data Science

R Fundamentals: Parts 1-4

March 8, 2022, 10:00am
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.

Infosession: D-Lab Data Science Fellowship (2024-2025)

April 11, 2024, 3:00pm
The D-Lab is seeking applications for the 2024-2025 cohort of Data Science Fellows. This infosession will give you an in-depth look at the D-Lab Data Science Fellowship and an opportunity for you to ask questions about the program that may be helpful to your application process to become a Fellow!

Qualtrics Fundamentals

February 15, 2023, 5:00pm
Qualtrics is a powerful online tool available to Berkeley community members that can be used for a range of data collection activities. Primarily, Qualtrics is designed to make web surveys easy to write, test, and implement, but the software can be used for data entry, training, quality control, evaluation, market research, pre/post-event feedback, and other uses with some creativity.

R Fundamentals: Parts 1-4

December 4, 2023, 10:00am
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.

Python Text Analysis: Topic Modeling

April 13, 2022, 3:00pm
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.

Python Machine Learning for Data Science Discovery

March 22, 2023, 7:00pm
Overview of Machine learning, Methods of Linear Regression, Logistic Regression (Classification), and Data Preprocessing. The workshop will consist of a live coding demo with a live question-answer session.

Python Fundamentals: Parts 1-4

October 26, 2021, 2:30pm
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.

R Fundamentals: Parts 1-4

August 15, 2022, 10:00am
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.

Qualtrics Fundamentals

December 3, 2021, 2:00pm
Qualtrics is a powerful online tool available to Berkeley community members that can be used for a range of data collection activities. Primarily, Qualtrics is designed to make web surveys easy to write, test, and implement, but the software can be used for data entry, training, quality control, evaluation, market research, pre/post-event feedback, and other uses with some creativity.

Python Text Analysis: Topic Modeling

April 4, 2024, 10:00am
In this part, we study unsupervised learning of text data. This is a stand alone work that builds from the two-part text analysis series.