Data Science

Demystifying AI

May 5, 2025, 2:30pm
In this workshop, we provide a basic and relatively non-technical introduction to the foundational concepts underlying contemporary AI tools. First, we’ll cover the the fundamentals of AI, Machine Learning, and Neural Networks/Deep Learning. Then, we’ll examine the capabilities and limitations of contemporary AI tools such as ChatGPT, Claude, and Perplexity, and outline best practices for the use of such tools.

Git Fundamentals

May 8, 2025, 10:00am
This introductory workshop covers basics of Git using command line(Bash). We will cover key concepts and workflows, including version control, repository creation, branching, merging, and collaboration. You'll gain hands-on experience navigating Git, managing repositories, and contributing to projects, making it easier to streamline your work and collaborate with others.

R SQL Fundamentals

April 28, 2025, 3:00pm
In this workshop, we provide an introduction to using SQL to query and retrieve data from relational databases in R. First, we’ll cover what relational databases and SQL are. Then, we’ll use different packages in R to navigate relational databases using SQL.

Python GPT Fundamentals

March 4, 2025, 10:00am
This workshop offers a general introduction to the GPT (Generative Pretrained Transformers) model. No technical background is required. We will explore the transformer architecture upon which GPT models are built, how transformer models encode natural language into embeddings, and how GPT predicts text.

Qualtrics Fundamentals (90 minutes)

May 16, 2025, 10:00am
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.

LLMs for Exploratory Research

March 20, 2025, 10:00am
In a fast evolving artificial intelligence landscape, LLMs such as GPT have become a common buzzword. In the research community, their advantages and pitfalls are hotly debated. In this workshop, we will explore different chatbots powered by LLMs, beyond just ChatGPT. Our main goal will be to understand how LLMs can be used by researchers to conduct early-stage (or exploratory) research. Throughout the workshop, we will discuss best practices for prompt engineering and heuristics to evaluate the suitability of an LLM's output for our research purposes. Though the workshop primarily focuses on early-stage research, we will briefly discuss the use cases of LLMs in later stages of research, such as data analysis and writing.

Lauren Chambers

Consultant
School of Information

Lauren Chambers is a Ph.D. student at the Berkeley School of Information, where she studies the intersection of data, technology, and sociopolitical advocacy with Prof. Deirdre Mulligan. Previously Lauren was the staff technologist at the ACLU of Massachusetts, where she explored government data in order to inform citizens and lawmakers about the effects of legislation and political leadership on our civil liberties. Lauren received her Bachelor's from Yale in 2017, where she double-majored in astrophysics and African American studies, and she spent two years after graduation in...

Sanjana Gajendran

Consultant
MIMS

I'm a second year MIMS Student with a focus on Data Science and Natural Language Processing. During the Summer 2023, I interned at Genentech as a Data Science Intern.

Thomas Lai

Consultant
School of Information

I am a Product Engineer passionate about applying engineering, data science, machine learning, and problem-solving principles to improve device performance and solve complex challenges. With experience in statistical analysis, lab bench automation, and Python scripting, I have developed a strong technical skill set that allows me to make meaningful contributions to any project. Beyond my work, I am also passionate about exploring new topics and ideas, from the latest technology trends to how to improve the overall well-being of humans. I enjoy applying the first principle to any...

Nicolas Nunez-Sahr

Consultant
Statistics

I lived in Santiago, Chile until I graduated from high school, and then moved to the US for undergrad at Stanford, where I obtained a Bachelor’s degree from the Statistics Department. I then worked as a Data Scientist in an NLP startup that was based in Bend, OR, which analyzed news articles. I love playing soccer, volleyball, table tennis, flute, guitar, latin music, and meeting new people. I want to get better at mountain biking, whitewater kayaking, chess and computer vision. I find nature astounding, and love finding sources of inspiration.