Professional Development Events

Advance your career as an effective, inclusive leader in STEM through this four-part series brought to you by the New York Academy of Sciences with special guest speakers from Pfizer senior leadership. Effective leadership is a key skill for all STEM professionals, but it is often difficult to define and practice. It requires developing and honing a range of personalized skills beyond the technical knowledge acquired from pursuing a degree or working in a lab or school. Aligning these skills with an individual’s values and strengths empowers them to be a positive change agent in the world, uplifting people within and outside a single organization. This four-part series of bite-sized learning webinars are designed to build key skills as a change maker. Participants will have the opportunity to attend the webinars live or on demand. Registration required.

Are you teaching this summer? This workshop will help you develop your course syllabus and curriculum as well as cover general tips and strategies for teaching compressed courses. While primarily designed for GSIs teaching in summer 2024, all GSIs interested in learning about compressed course design are welcome to attend! Please note this is a 2 hour workshop.

This workshop introduces students to scikit-learn, the popular machine learning library in Python, as well as the auto-ML library built on top of scikit-learn, TPOT. The focus will be on scikit-learn syntax and available tools to apply machine learning algorithms to datasets. No theory instruction will be provided.

Are you are a Latin American student planning to pursue an International MBA this year? Are you considering a career in consulting after completing your MBA? Join us on April 18th for a Q&A session where you'll gain insights from our consultants about their MBA journey, recruitment process, preparation, and invaluable tips for launching a career in consulting. Don't miss out on this valuable opportunity to connect with McKinsey colleagues and gain a deeper understanding of the consulting industry.  

The GSI Center’s Workshops on Teaching for GSIs cover a wide variety of topics related to university teaching and the GSI experience. The purpose of the series is to offer GSIs, and other graduate students interested in teaching, opportunities for hands-on learning and practical discussion about pedagogy.

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching with LLMs, Kimberly Vinall, Emily Hellmich, Genevieve Smith, and Ben Spanbock will lead a dialogue on the potential of LLMs in reshaping educational landscapes. It discusses educational challenges such as AI literacy, academic integrity, biases, hallucinations, and privacy issues, as well as opportunities such as accessibility and democratization. Questions we will be addressing include: How can we cultivate openness in class about students using LLMs and GenAI? Will LLMs fundamentally alter the importance of remembering knowledge and learning? Are LLMs fundamentally different from other information technologies like Wikipedia? How to cultivate openness in class about students using LLMs and GenAI? LLM working Group sessions will be interactive, encouraging participants to share their experiences, pose questions, and collaboratively explore the challenges and potential of these technologies in their respective fields. Please send in your questions ahead of time for priority consideration – you can use this Google Form to let us know what’s on your mind. We review all submitted questions but may need to shorten, consolidate, or clarify them for discussion. We encourage everyone to participate, regardless of their experience level with LLMs and GenAI. The LLM Working Group is a welcoming and supportive community for all. This is a hybrid event. In-person seating is limited to 35.

The LLM Working Group is a community founded to facilitate conversations about Large Language Models (LLMs) and Generative AI within academia. This 4-part series will provide fundamental knowledge of LLMs, and generate conversation about the promises and challenges of LLMs in different facets of academic work. In the second session, Teaching with LLMs, Kimberly Vinall, Emily Hellmich, Genevieve Smith, and Ben Spanbock will lead a dialogue on the potential of LLMs in reshaping educational landscapes. It discusses educational challenges such as AI literacy, academic integrity, biases, hallucinations, and privacy issues, as well as opportunities such as accessibility and democratization. Questions we will be addressing include: How can we cultivate openness in class about students using LLMs and GenAI? Will LLMs fundamentally alter the importance of remembering knowledge and learning? Are LLMs fundamentally different from other information technologies like Wikipedia? How to cultivate openness in class about students using LLMs and GenAI? LLM working Group sessions will be interactive, encouraging participants to share their experiences, pose questions, and collaboratively explore the challenges and potential of these technologies in their respective fields. Please send in your questions ahead of time for priority consideration – you can use this Google Form to let us know what’s on your mind. We review all submitted questions but may need to shorten, consolidate, or clarify them for discussion. We encourage everyone to participate, regardless of their experience level with LLMs and GenAI. The LLM Working Group is a welcoming and supportive community for all. This is a hybrid event. In-person seating is limited to 35.

Deepen your knowledge of inclusive teaching practices by exploring the Universal Design for Learning framework. Join us to learn more about how to center inclusion in your pedagogy, and apply this understanding through evaluating examples and resources.

Interested in restricted Census or partnering RDC agency (AHRQ, BLS, BEA, NCHS) data use? This one-hour introductory workshop will provide an overview of the Berkeley Federal Statistical Research Data Center, with no prior experience assumed. Attendees will learn about the national RDC network, how to access information online about restricted Census data, and how to navigate proposal development.

Advance your career as an effective, inclusive leader in STEM through this four-part series brought to you by the New York Academy of Sciences with special guest speakers from Pfizer senior leadership. Effective leadership is a key skill for all STEM professionals, but it is often difficult to define and practice. It requires developing and honing a range of personalized skills beyond the technical knowledge acquired from pursuing a degree or working in a lab or school. Aligning these skills with an individual’s values and strengths empowers them to be a positive change agent in the world, uplifting people within and outside a single organization. This four-part series of bite-sized learning webinars are designed to build key skills as a change maker. Participants will have the opportunity to attend the webinars live or on demand. Registration required.

This interactive workshop series is your complete introduction to programming in R for people with little or no previous programming experience. It covers the basics of using RStudio, creating variables, working with data frames, and starting to analyse your data using summary statistics and data visualization. After completing this workshop series you will be able to: Navigate R Studio Open data in R and work with it in data frames using tidyverse Distinguish between different variable types Visualize data using ggplot Inspect documentation to deal with error messages R Fundamentals has 4 parts. Each of the parts takes 2 hours, and is delivered in a lecture-style coding walk through interrupted by challenge problems and a break. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. The workshop series is structured as follows: Part 1: Introduction to R and RStudio Part 2: Data frames and variable types Part 3: Manipulating data frames Part 4: Data visualizations and custom functions

This three-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. The complete Python Fundamentals series has 6 parts. Each of the parts takes 2 hours, and is delivered in a lecture-style coding walkthrough interrupted by challenge problems and a break. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Parts 1-3 are intended for the complete beginner in Python. We will go over the basics of Python in Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas: Part 1: Introduction to Jupyter and Python, Variables Part 2: Data Types and Structures Part 3: Introduction to Pandas After completing parts 1-3, you will be able to do basic operations in Python. You will know how to navigate Jupyter Notebooks, how to work with common data types and structures, methods, and basic operations in Pandas. You will have the minimum requirements to continue to other D-Lab workshops such as Python Data Wrangling or Python Data Visualization.

This interactive workshop series is your complete introduction to programming in R for people with little or no previous programming experience. It covers the basics of using RStudio, creating variables, working with data frames, and starting to analyse your data using summary statistics and data visualization. After completing this workshop series you will be able to: Navigate R Studio Open data in R and work with it in data frames using tidyverse Distinguish between different variable types Visualize data using ggplot Inspect documentation to deal with error messages R Fundamentals has 4 parts. Each of the parts takes 2 hours, and is delivered in a lecture-style coding walk through interrupted by challenge problems and a break. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. The workshop series is structured as follows: Part 1: Introduction to R and RStudio Part 2: Data frames and variable types Part 3: Manipulating data frames Part 4: Data visualizations and custom functions

Calling all digital humanities enthusiasts! If you are interested in presenting for this session please complete this google form. We encourage everyone to participate, regardless of your experience level. The DH Working Group is a welcoming and supportive community for all things digital humanities. About the Digital Humanities Working Group The UC Berkeley Digital Humanities Working Group is a research community founded to facilitate interdisciplinary conversations in the digital humanities and cultural analytics. Our gatherings are participant driven and provide a place for sharing research ideas (including brainstorming new ideas and receiving feedback from others), learning about the intersection of computational methods and humanistic inquiry, and connecting with others working in this space at Berkeley. We welcome grad students, faculty, and staff from all disciplinary backgrounds regardless of whether you are a beginner or an expert in empirical and data-driven methods. Working group meetings may include participants sharing work on current or future research, open discussions about theoretical, methodological or other challenges (e.g., data collection), invited speakers, and social mixers. Research at any stage of development (including nascent) is welcome for discussion. The Digital Humanities Working Group is led by Tim Tangherlini (Department of Scandinavian) and David Bamman (School of Information), and sponsored by D-Lab: Claudia von Vacano, Aaron Culich, Finley Golightly, and the UTech staff.

Calling all digital humanities enthusiasts! End-of-the-year celebration! Lightning talk for our fifth DHWG meeting: “Tracking Microchanges: On the Evolution of the Novelistic Scene” - Nicholas Paige, Professor of French, presents an analytical examination of "scenes" in the novel from the early 1800s. If you are interested in presenting for this session, please complete this google form. We encourage everyone to participate, regardless of your experience level. The DH Working Group is a welcoming and supportive community for all things digital humanities. About the Digital Humanities Working Group The UC Berkeley Digital Humanities Working Group is a research community founded to facilitate interdisciplinary conversations in the digital humanities and cultural analytics. Our gatherings are participant-driven and provide a place for sharing research ideas (including brainstorming new ideas and receiving feedback from others), learning about the intersection of computational methods and humanistic inquiry, and connecting with others working in this space at Berkeley. We welcome grad students, faculty, and staff from all disciplinary backgrounds regardless of whether you are a beginner or an expert in empirical and data-driven methods. Working group meetings may include participants sharing work on current or future research, open discussions about theoretical, methodological or other challenges (e.g., data collection), invited speakers, and social mixers. Research at any stage of development (including nascent) is welcome for discussion. The Digital Humanities Working Group is led by Tim Tangherlini (Department of Scandinavian) and David Bamman (School of Information), and sponsored by D-Lab: Claudia von Vacano, Aaron Culich, Finley Golightly, and the UTech staff