Events

This clinic is intended for STEM graduate students and postdocs who are CURRENTLY on the job market or planning to be in the fall. Get feedback on your interview skills, and prepare for online and screening interviews. Sign up for a time slot for 25 minute individual advising session. There are slots for 25 people. YOU MUST sign up ahead of time to participate; deadline to register is March 1, 2023. The event runs from March 4th to March 8th. 

The Global Women in Data Science (WiDS) Conference is an annual technical conference based at Stanford University, which brings together data scientists and professionals in adjacent fields from around the globe to discuss the latest research and applications of data science in a broad set of domains. Participants learn how leading-edge companies are leveraging data science for success and connect with potential mentors, collaborators, and others in the field. WiDS Berkeley is an independent event organized by the Berkeley School of Information and other UC Berkeley partners as part of the annual WiDS Worldwide conference, the WiDS Datathon, and an estimated 200 WiDS Regional Events worldwide. Everyone is invited to attend all WiDS conference and WiDS Datathon Workshop events which feature outstanding women doing outstanding work. All genders are invited to participate in the conference, which features exclusively female speakers.

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

While colleges can foster discourse and promote inclusion, polarizing topics can lead to conflict on campus. How can universities mitigate contention when controversial speakers or protests occur on campus? The responses to the Israel-Hamas war over the past several months highlight this concern and the need for institutions to consider how they can de-escalate conflicts and bring students together. In the upcoming Virtual Forum, Ian Wilhelm, deputy managing editor, will host a panel of national experts to discuss how to prepare for this unique challenge. Join “Building Civil Campus Conversations” on March 5th at 11 am PST.

Interested in advancing equity within the courses that you teach? Eager to try grading in new or different ways? We invite you to network with like-minded colleagues who have explored different strategies for equitable grading. In small roundtable discussions, participants will have the chance to meet with different instructors who have redesigned their grading to foster greater equity in student learning and outcomes. Instructors will be encouraged to share their own experiences and challenges with grading, as well as collaboratively brainstorm possible solutions to common problems in grading. Through these shared stories, instructors may begin to see how they can take small, but manageable steps toward adopting a new grading approach. At the end of this session, you will: Build a supportive community around equitable or alternative grading practices. Share strategies for equitable grading across and within disciplines. Identify an opportunity to revise or add a graded component of your course for equity. Everyone in the UC Berkeley instructional community is welcome to join the chat! This event is hosted by Research, Teaching, and Learning (RTL) and the College of Engineering EMPOWER Program and is one of a three-part series focused on Equitable Grading Strategies. Please consider also enrolling in the other two events: The History and Future of Grades - Teaching & Learning Journal Club and Putting Equitable Grading into Practice - Assignment Clinic. This hybrid event will be held in person in 117 Dwinelle Hall (Academic Innovation Studio) and also on Zoom. Please RSVP to get the Zoom invite.   Light snacks will be available for in-person participants. We kindly request that you register no later than 3 days in advance if you're attending in person, to help us arrange catering.  This coffee chat will run for 60 minutes, with an additional 30 minutes reserved for informal networking amongst participants and invited guests. ➡️ Register for this event here!⬅️ ***Registration for this session will close two hours before the session for remote participants***

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 Geospatial Fundamentals: Part 1 This workshop is the first one of the two-part series on using Python for fundamental geospatial analysis and visualization. After this workshop, you will be able to: Recognize different forms of geospatial data and coordinate reference system (CRS), Use GeoPandas and matplotlib libraries to map and analyze spatial data. Python Geospatial Fundamentals: Part 2 This workshop is the second one of the two-part series on using Python for fundamental geospatial analysis and visualization. After this workshop, you will be able to: Apply more advanced Python libraries for interactive visualization. Choose domain-specific spatial datasets to create your own maps. Knowledge Requirements You'll probably get the most out of this workshop if you have a basic foundation in Python and Pandas, similar to what you would have from taking the D-Lab Python Fundamentals workshop series. Here are a couple of suggestions for materials to check out prior to the workshop. D-Lab Workshops: Python Fundamentals Python Data Wrangling and Manipulation with Pandas

This workshop provides an introduction to visualization with Python. We will cover visualization principles and plotting with Matplotlib and Seaborn, working through examples in a Jupyter notebook and documentation of each plotting package. We’ll also learn about styles and customizing plots. Throughout the workshop, we’ll discuss the plot types best suited for particular kinds of data. The following plot types will be covered: Histogram Barplot Boxplot Scatterplot Lineplot Subplot We'll also learn about styles and customizing plots. Throughout the workshop, we'll discuss the plot types best suited for particular kinds of data.