Events

In this workshop, we cover how to extract data from the web with APIs using Python. APIs are often official services offered by companies and other entities, which allow you to directly query their servers in order to retrieve their data. Platforms like The New York Times, Twitter and Reddit offer APIs to retrieve data. When APIs are not available, one can turn to web scraping. If you want to learn how to do web scraping in Python, attend the D-Lab Python Web Scraping Workshop. We will assume a basic knowledge of Python. We recommend attending D-Lab's Python Fundamentals and Python Data Wrangling prior to this workshop. We additionally recommend a basic understanding of HTML and CSS. Prerequisites: We recommend attending D-Lab's Python Fundamentals and Python Data Wrangling prior to this workshop. We additionally recommend a basic understanding of HTML and CSS.

Calling all digital humanities enthusiasts! 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. The March meeting's theme is digital mapping and is co-sponsored by the Earth Sciences and Map Library. We have Mr. Stace D Maples from Stanford's David Rumsey Collection visiting to talk about the project before opening up the floor to broader discussion. Lunch is provided. If you're interested in giving a lightning talk or workshopping your research, please sign up here. What is a lightning talk? A lightning talk is a short, fast-paced presentation that typically lasts 5-10 minutes. It's a great way to share your research with a wider audience and get feedback from your peers. 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.

This is a three-hour introductory workshop that will provide an overview of Excel, with no prior experience assumed. Attendees will learn how to use functions for handling data and making calculations, how to build charts and pivot tables, and more. The workshop includes a lecture-style walkthrough of each concept, combined with challenge problems to apply each concept to a real-world data analysis application. Instructors and TAs will provide support for students using Excel on either Windows or Mac, as well as for students using Google Sheets.

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.

In this workshop, we will convey the basics of deep learning in Python using keras on image datasets. You will gain a conceptual grasp of deep learning, work with example code that they can modify, and learn about resources for further study. We start with a review of what deep learning is and then unpack what neural networks are and how they work. We then jump straight into Python, using the Keras library to build neural networks. We will explore how different architectures affect performance of predicting handwritten digit images.

In this workshop, we cover how to scrape data from the web using Python. Web scraping involves downloading a webpage's source code and sifting through the material to extract desired data. Web scraping is typically only done when Web APIs are not available. Platforms like Twitter, Reddit, or The New York Times offer APIs to retrieve data. If you want to learn how to use web APIs in Python, see D-Lab's Python Web APIs workshop. We will assume a basic knowledge of Python. We recommend attending D-Lab's Python Fundamentals and Python Data Wrangling prior to this workshop. We additionally recommend a basic understanding of HTML and CSS.

Classroom observation tools provide an objective method for evaluating the use of active learning strategies in college classrooms (Lund et al., 2015). These tools allow instructors to document and assess their teaching practices, track improvements over time, and compile evidence for teaching portfolios, faculty position applications, and tenure reviews. Over the past two decades, various protocols have been developed to systematically analyze classroom instruction. One widely used method is the Classroom Observation Protocol for Undergraduate STEM (COPUS; Smith et al., 2013). Originally designed for STEM disciplines, COPUS has been applied across many fields due to its structured approach to capturing classroom dynamics. In this workshop, participants from all disciplines will receive hands-on training in COPUS, which categorizes classroom activities without making subjective judgments about teaching quality. Observers record instructor and student behaviors using 25 distinct codes at 2-minute intervals, creating a detailed snapshot of classroom interactions. By the end of the session, attendees will be equipped to use COPUS effectively to analyze and enhance instructional practices in their own classrooms. Participants will also learn how to use COPUS data to: Reflect on their teaching practices Identify opportunities to incorporate active learning strategies Track and document teaching adaptations over time Explore how COPUS supports evidence-based teaching and improves student engagement Bring your lunch and make the most of your lunch break with us!

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. This overview will introduce a simple workflow using the system with an orientation to the main interfaces for web survey design, sample management, corresponding with sample members, and exporting data at the end of the field period. Examples from completed surveys in public health, economics, program evaluation, and other disciplines will be incorporated in the overview. This workshop will introduce students to the basics of designing a survey instrument using the Qualtrics platform, such as randomization and survey flow. We will also cover more advanced topics like implementing embedded data and using javascript, as well as tips and tricks on how to use your design to maximize the number of quality responses you get.

This workshop addresses the unique challenges and opportunities of implementing active learning strategies in large, introductory lecture settings, which are crucial as they often mark the beginning of a student's journey into a specific discipline or way of thinking. Research in educational pedagogy supports the effectiveness of active learning, particularly in large classes. However, students in large classes might feel skeptical (or curious!) about engaging in active learning, given that large classes often rely primarily on lecture. In this workshop, we will explore strategies for incorporating active learning into large classes, as well as some techniques for fostering a shared understanding with students about your instructional choices. This session will run for 30 minutes, with an additional 15 minutes reserved for questions.

Join us in a supported workspace to research, prepare and apply for your ideal internship. Learn about opportunities for paid internships, micro-internships and more. Bring your laptop and friends to collaborate and get real-time feedback on internship opportunities, optimize your internship search and learn about additional tips and resources.

A key step in the job search process is understanding the skills needed for different roles. In this workshop, our facilitators will guide you in identifying your transferable academic skills and developing new competencies to expand your career options. Virtual workshop hosted by GradPro. Learn more and sign-up for the workshop in the registration form.

This three-hour workshop will cover charts in more detail, review pivot tables, and the widely-used VLOOKUP function. We recommend first taking the introductory workshop Excel Data Analysis: Introduction.

In this workshop, we provide an overview of conducting U.S. Census data analysis and visualization in R. First, we’ll cover the basic concepts of U.S. Census Data. Then, we’ll demonstrate how to call the census data API directly from R by using the R tidycensus package.

Join us for a special session on using iClicker’s AI Question Creator, a new tool that leverages generative AI to craft unique, discipline-specific questions tailored to your teaching needs. This session will guide you through constructing questions that aim to enhance student engagement and elevate discussions in your classroom or assessments, as well as confidently integrate the tool into your teaching to save time and elevate classroom interactions. The session includes a 30-minute presentation followed by 30 minutes dedicated to Q&A and open discussion, offering ample time to address your specific questions, share ideas with fellow instructors, as well as provide initial feedback to the iClicker team.

Networking can feel intimidating, but having a clear approach makes all the difference! In this workshop, you’ll gain practical tips for identifying professional networks, conducting informational interviews, and creating a personalized plan to kick-start your networking journey. Virtual workshop hosted by GradPro. Learn more and sign-up for the workshop in the registration form.

Are you sick of working all the time without making progress on your writing projects? Are you tired of your deadline-driven, binge-and-bust writing routine? Do you wish you could develop a healthy, consistent, daily writing routine that would allow you to meet your department’s expectations for tenure and promotion? In this webinar you'll learn: The three biggest myths about writing that hobble new faculty productivity The surprising difference between struggling new faculty members and those who are designated as "rising stars" The 30-minute strategy that will increase your writing productivity AND decrease your stress, anxiety and guilt

This three-part workshop will prepare participants to move forward with research that uses text analysis, with a special focus on social science applications. We explore fundamental approaches to applying computational methods to text in Python. We cover some of the major packages used in natural language processing, including scikit-learn, NLTK, spaCy, and Gensim. Part 1: Preprocessing. How do we standardize and clean text documents? Text data is noisy, and we often need to develop a pipeline in order to standardize the data to better facilitate computational modeling. You will learn common and task-specific operations of preprocessing, becoming familiar with commonly used NLP packages and what they are capable of. You will also learn about tokenizers, and how they have changed since the advent of Large Language Models. Part 2: Bag-of-words. In order to do any computational analysis on the text data, we need to devise approaches to convert text into a numeric representation. You will learn how to convert text data to a frequency matrix, and how TF-IDF complements the Bag-of-Words representation. You will also learn about parameter settings of a vectorizer and apply sentiment classification to vectorized text data. Part 3: Word Embeddings. Word Embeddings underpin nearly all modern language models. In this workshop, you will learn the differences between a bag-of-words representation and word embeddings. You will be introduced to calculating cosine similarity between words, and learn how word embeddings can suffer from biases. The materials for this workshop series are designed to build on each other. Part 2 assumes familiarity with the content from Part 1, and Part 3 similarly requires understanding of both preceding parts. Prerequisites: We recommend attending Python Fundamentals, Python Data Wrangling, and Python Machine Learning Fundamentals prior to this workshop.

💡 Learn how educators are adapting to the changing landscape of education and inspiring the next generation of learners! Discover the latest trends and best practices in education at our upcoming event featuring Kyle Cohen (@mr.kylecohen), a Teach For America Greater Cleveland alum who spent six years inspiring fourth graders and now serves as an Assistant Principal. Kyle's journey, from summer camp counselor to school leader, has given him an understanding of the challenges and rewards of working in education. He will share his experiences and offer valuable advice on building the schools our kids deserve.

Public speaking, conveying complex information to non-experts, managing teams, evaluating the work of junior colleagues — these are among the many skills GSIs develop in their teaching, and these skills are eminently transferable to career settings in higher education, private industry, non-profits, or governmental agencies. Register

Discuss professional disclosure of disability with two successful DSP alumni.

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.

Learn about careers in science education and outreach from a Berkeley PhD Chemistry alum! At this event you’ll hear about making the transition from benchwork to a career using advanced scientific training to broaden access to science to youth and the public. March 20, 2025 in person, Stanley Hall 11:00am - noon - career talk, moderated chat/discussion - Room 177 Stanley Hall Mentoring in small groups - 3-5 people, location Stanley hall, room tba 1:30-2:05 - mentoring 1 2:10-2:45 - mentoring 2 3:00-3:35- mentoring 3 Speaker Bio: Lee Bishop serves as the Biotechnology Lead and Design Strand Lead at the Lawrence. Lee works to broaden access to science by creating innovative learning experiences that present science as a human endeavor that can be equal parts fun and challenging. He is particularly interested in finding ways for youth and families to add their ideas and values to conversations around how science can be used to address societal challenges. Lee leads the Hands-on Biotech exhibit space and leads the design of other cross-organizational initiatives. Lee earned his B.S. in Chemistry from Case Western Reserve University and his Ph.D. in Chemistry from UC Berkeley.

In this virtual workshop you will learn techniques to keep yourself organized and apply for positions (internships or jobs) in a way that balances application tailoring and volume. Participants will be provided tools, supportive practices, and resources to make organizing your job/ internship search more fulfilling and efficient.  We will cover: How to ethically use AI systems such as Chat GPT and Ramped to support your applications Resources such as a Job Application Tracking Sheet Why it is important to save the job description Why it is helpful to think of “time spent” applying vs number of applications …and more helpful tips to support your job and or internship applications