Upcoming Events

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. Each of the parts is divided into a lecture-style coding walkthrough interrupted by challenge problems, discussions of the solutions, and breaks. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. Prerequisites: None Part 1: Introduction Learn how to navigate the R Studio environment. You will also learn how to store data, characteristics of basic data types and data, the importance of data frames (think Excel spreadsheets), and how to save your work. Part 2: Subsetting and Reshaping You will then be introduced to loading data from files and various ways to subset it with an emphasis on bracket notation. You will also learn how to use logical vectors, search for and subset missing data, and merge data frames. Part 3: Data Exploration and Visualization Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots using ggplot. Part 4: Control Structures In the final part, we will cover how to use programming control structures such as functions, for-loops, and if-else statements to make more readable and re-usable code. Workshop Materials: https://github.com/dlab-berkeley/R-Fundamentals Software Requirements: Installation Instructions for R and RStudio

In this webinar, Dr. Flores and Dr. Olcott will discuss how to negotiate salaries, leave, and other elements of employment at an academic institution. They will consider how to assess academics' leverage, what elements might constrain possibilities for obtaining a better offer, and how to know when you've exhausted the negotiating process. Join Zoom Meeting Meeting ID: 858 3421 3664 Passcode: 504153

This workshop is designed for graduate students who are interested in improving their statements ​of teaching philosophy through feedback​ ​from peers. Workshop participants will exchange statements of teaching philosophy and provide​ ​and receive input. Participants must bring two copies of a draft of their statement of teaching philosophy to participate in the workshop.

Join us for a workshop focused on assignments, quizzes, and grading to learn how to take advantage of more advanced features that will help you use bCourses to its fullest, freeing up your time for what matters most. In this workshop, you will learn how to: Use bCourses's grading tools to evaluate students effectively. Set up simple rubrics to help you grade. Use SpeedGrader to grade faster. Understand and apply grading rules that work for your class. Manage and interpret the Gradebook. Access resources and support to address any grading questions or challenges. This session will be held via Zoom. Please register to get the Zoom link. ➡️ Register for this event here!⬅️

Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping vector data, which encodes location as points, lines and polygons. Part I: Core concepts, vector data, and plotting Basic geospatial concepts Basic vector data Geospatial data structures (the sf package) Basic plotting (base::plot and the ggplot3 package) Managing coordinate reference systems (CRS) Advanced plotting (the tmap package) Map overlays Part II: Spatial analysis Spatial measurement queries Spatial relationship queries Buffer analysis Spatial and non-spatial joins Aggregation Continued mapping practice Prerequisites: D-Lab’s R Fundamentals or equivalent knowledge; previous experience with base R is assumed and basic familiarity with the tidyverse. Workshop Materials: https://github.com/dlab-berkeley/R-Geospatial-Fundamentals Software Requirements: Requirements for R and RStudio

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. Prerequisites: D-Lab’s Python Fundamentals introductory series or equivalent knowledge. Workshop materials: https://github.com/dlab-berkeley/Python-Machine-Learning-Fundamentals Software Requirements:Installation Instructions for Python Anaconda Is Python Not working on your laptop? Attend the workshop anyway, we can provide you with a cloud-based solution until you figure out the problems with your local installation.

Learning environments can promote student belonging, academic  identity, and joy using inclusive teaching practices. This workshop continues our critical discussion of ways to incorporate inclusive teaching, famed by Universal Design for Learning (UDL). UDL guides instructors to proactively implement multiple ways to demonstrate understanding, engage in content, and have content represented. Through this UDL lens, this workshop explores how joy in learning creates resiliency, intrinsic motivation, meaning-making, and deeper learning. It is also linked to truth, beauty, aesthetics, artful thinking, wonderment, and activities where students feel personal fulfillment and have opportunities to create solutions to real-world problems (Muhammad, 2023). Join our workshop as we provide stories of deep learning, teaching, and researching that use joy-informed pedagogy to activate student agency, promote healing, and build community. Our discussion will revolve around these critical thinking questions: Where does joy fit into learning, and how does it manifest in learning? Can deep learning happen without joyful discoveries, deeper self-awareness, transformation? This hybrid event will be held in person in 117 Dwinelle Hall (Academic Innovation Studio) and also on Zoom. Please RSVP for the Zoom link, and if you're joining us on-site, please make sure to register as well. This workshop will also include an optional 45-minute Q&A open lab directly after the workshop for any in-person participant wanting to work towards inclusive teaching goals in their own courses. ➡️ RSVP for this event here!⬅️

Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping vector data, which encodes location as points, lines and polygons. Part I: Core concepts, vector data, and plotting Basic geospatial concepts Basic vector data Geospatial data structures (the sf package) Basic plotting (base::plot and the ggplot3 package) Managing coordinate reference systems (CRS) Advanced plotting (the tmap package) Map overlays Part II: Spatial analysis Spatial measurement queries Spatial relationship queries Buffer analysis Spatial and non-spatial joins Aggregation Continued mapping practice Prerequisites: D-Lab’s R Fundamentals or equivalent knowledge; previous experience with base R is assumed and basic familiarity with the tidyverse. Workshop Materials: https://github.com/dlab-berkeley/R-Geospatial-Fundamentals Software Requirements: Requirements for R and RStudio

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. Prerequisites: D-Lab’s Python Fundamentals introductory series or equivalent knowledge. Workshop materials: https://github.com/dlab-berkeley/Python-Machine-Learning-Fundamentals Software Requirements: Installation Instructions for Python Anaconda Is Python Not working on your laptop? Attend the workshop anyway, we can provide you with a cloud-based solution until you figure out the problems with your local installation.

Hear from a panel of experts—an acquisitions editor, a scholarly book author, and an author rights expert—about the process of turning your dissertation into a book. You’ll come away from this panel discussion with practical advice about revising your dissertation, writing a book proposal, approaching editors, signing your first contract, and navigating the peer review and publication process.

The goal of this workshop is to build intuition for deep learning by building, training, and testing models in Python. Rather than a theory-centered approach, we will evaluate deep learning models through empirical results. 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 the performance of predicting handwritten digit images. Lastly, we explore a specific flavor of neural networks, the convolutional neural network. We review how it’s different from a standard vanilla neural network, and build different architectures to test how well they perform on the classification of animal and vehicle image classification. Prerequisites: D-Lab's Python Machine Learning Fundamentals (6 hours) series or equivalent introductory machine learning knowledge. Workshop Materials: https://github.com/dlab-berkeley/Python-Deep-Learning.

It is said that 80% of data analysis is spent on the process of cleaning and preparing the data for exploration, visualization, and analysis. This R workshop will introduce the dplyr and tidyr packages to make data wrangling and manipulation easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful tasks. Prerequisites: D-Lab’s R Fundamentals or equivalent knowledge; previous experience with base R is assumed. Workshop Materials: https://github.com/dlab-berkeley/R-Data-Wrangling Software Requirements: Installation Instructions for R and RStudio

You’ve done your homework, talked to working professionals in your emergent field, and are ready to begin submitting applications. Learn how to present the skills and experience you’ve developed in grad school and before in the most clear and compelling manner to your potential future employer.

The goal of this workshop is to build intuition for deep learning by building, training, and testing models in Python. Rather than a theory-centered approach, we will evaluate deep learning models through empirical results. 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 the performance of predicting handwritten digit images. Lastly, we explore a specific flavor of neural networks, the convolutional neural network. We review how it’s different from a standard vanilla neural network, and build different architectures to test how well they perform on the classification of animal and vehicle image classification. Prerequisites: D-Lab's Python Machine Learning Fundamentals (6 hours) series or equivalent introductory machine learning knowledge. Workshop Materials: https://github.com/dlab-berkeley/Python-Deep-Learning.

HOW WILL YOU INFLUENCE THE WORLD? Let Morgan Stanley Equity Research challenge your perceptions about Wall Street. We are dynamic in our thinking because every member of our team is unique. Hear from Kristine Liwag (Executive Director, Lead Analyst of Aerospace & Defense), MaryAnne Zhao (Vice President, Media and Entertainment), and Stefan Diaz (Associate, Tobacco and Packaged Food) as they share their career journey with you. Gain meaningful insight into what it is like to work at Morgan Stanley, our culture, and the work we do. You will hear first-hand what skills are required to succeed in Research. You will also have the opportunity to ask about what matters most to you and your career. If you want to learn how to influence the world, identify market moving trends, and be a thought-leader, join us at our MS Research Insight Webinar. We welcome your talent and ambition. Date: Thursday, November 16, 2023 Time: 6:00 pm – 7:00 pm (Eastern Time) We welcome all who are interested regardless of grade and major or discipline to register. REGISTER HERE Venue: Virtual - Zoom Learn more at www.morganstanley.com/campus

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.

Agency for Science, Technology and Research (A*STAR) is Singapore’s lead public sector agency driving economic-oriented research, advancing scientific discovery, and developing innovative technology. It will be hosting a series of information session at UC Berkeley, focusing on overseas Research Internships and Scholarships for both Undergraduates and Graduates. Please register here or contact Ms June Wang at [email protected] for more info!

This in-person group career chat is a place to discuss a range of techniques one may use to navigate internalized oppressions in the job search. We will use kyriarchy as an intersectional model of oppression as a multi identity experience. Students who have one or more marginalized identities related to any of the following are invited to join: Race, gender, sexual orientation, low income, disability, neurodivergence, ancestral heritages that have survived (or not survived) colonization, students who are parents and undocumented students are welcome to join. We will take as fact that career culture and the job search in North America at this time is located within systems such as capitalism, colonization, white supremacy, ableism, neurotypicality and other oppressive systems. We will take some time to unpack typical career experiences that reflect and enforce these systems to gain awareness. We will work through students lived experience(s) and will address scenarios brought up by students (past scenarios and future fears and or realities are all welcome) We will specifically focus on internalized oppressions for this session. Affinity based resources will also be shared. Students should come prepared to discuss group agreements prior to any shared experiences (we will co-create these). Techniques will range from somatic exercises (available to students of varying ability), community building, understanding personal values, how to lean into identity specific mentorship and other resources as needed. About the facilitator: Lily Ritchie (Career Counselor) is a white, cis-gendered woman with an invisible disability from a first generation, low income background, who currently holds education and middle class privileges'. She currently serves as the Arts & Humanities liaison within the College of Letters and Science and serves as the Berkeley Career Engagement liaison to both the The Gender Equity Resource Center and the Queer Alliance Resource Center. Limited to 20 students.

This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures. Prerequisites: D-Lab’s R Fundamentals or equivalent knowledge; previous experience with base R is assumed. Workshop Materials: https://github.com/dlab-berkeley/R-Data-Visualization Software Requirements:Installation Instructions for R and RStudio

Josh Yim received his PhD in Chemical and Systems Biology at Stanford from 2014-2020. His work in the Bogyo Lab focused on imaging tumors using chemical sensors. Through his experience with industry collaborations during graduate school, Josh developed a keen interest in business which led him to join BCG’s San Francisco office upon graduation. Josh consults biopharma, biotech, payers, and providers, focusing on R&D strategy development, portfolio optimization, and organization redesign, among other areas. Currently, Josh is doing a secondment at Johnson & Johnson, working to form partnerships with data science companies to support J&J’s R&D pipeline. Josh is excited to share his insights on making the transition from research to consulting.

As you might know, UC Berkeley is the top university in the number of companies founded by undergraduate alumni. Cal has been stepping up efforts to support the graduate students and postdocs aspiring to transition their research to building products at startups. Come attend this workshop to understand some of the resources, including fellowships, working space and mentorship that one would need to build a startup. We have three fantastic speakers, Prof. Dave Schaffer, Susan Abrahamson and Darren Cooke sharing the information and learnings.

Business development and research roles inside companies draw from a range of skills, knowledge and domain expertise. They are also significantly populated by PhDs and post-graduates around the world and can offer terrific career mobility. Dr. Ray Price has worked across many roles and brings fresh insight into what these jobs entail, as well as how you might land one. Ray is a pharma/biotech business development executive responsible for increasing sales and managing collaborative R&D agreements for Neuroservices Alliance by leading the commercial team. He has an MBA from INSEAD (2009), and has work experience in Japan, the US, and France. He also has a Ph.D. in Pharmacology from Vanderbilt University and extensive R&D experience. Finally, Ray is the founder and owner of a (profitable!) small business that performs solutions services (medical writing and editing) for non-native English speakers, with global clients in more than 10 countries.

During this workshop we will walk through and practice the Technical Interview and a Case-Tech Interview example. These examples will be guided by Capital One professionals trained in facilitating the interview process. A recruiter will also be on the call to answer any questions you may have. This workshop is intended to help candidates prepare for the following Students & Grads roles: Technology Internship Program and the Technology Development Program.

Find Your Future With Us! Drop in to learn about "Entry-Level" Natural Resource and Agriculture Related Job openings which are open the week of this event! We will highlight some information about these positions, their locations, and the best way to apply and be considered! Please note, this is intended for students and graduates who have a background, interest and degree in Biology, Natural Resources, Agriculture, and related sciences. Due to HR Requirements, applicants in non-science backgrounds will not be considered for the positions.

This panel will bring together UC alumni and current faculty to discuss STEM faculty hiring and share insights with the audience of STEM PhD trainees. Topics may include: Timeline for search(es), when to talk about your priorities as a couple, and who or what might provide assistance/support to you in the planning phase? When might be best to bring up a partner’s work needs/situation to potential employers? Do institutions provide any kind of dual career assistance? Is it ok to negotiate for benefits that affect a partner’s job options or work? Speakers include:  Ed Green, PhD, Director, QB3-Santa Cruz and Professor of Biomolecular Engineering, UC Santa Cruz Amy Pickering, PhD, Assistant Professor, Blum Center Distinguished Chair in Global Poverty and Practice, UC Berkeley Meng-meng Fu, PhD,  Assistant Professor of Cell Biology, Development and Physiology, UC Berkeley

Thank you for your interest in the "Time Management: Tips and Tools" workshop offered by Graduate Peer Support Providers at UC Berkeley. Join us for a chance to learn about tips and tools to help you management your time! In this workshop, we will cover the following topics: What is Time Management Time Management Tips The Big Three Strategies Time Management Tools Tackling Procrastination This workshop will take place on Thursday November 30th at 4:30PM on Zoom or in person. For those interested in attending in person, a location will be sent via email after registration. Please complete this registration form to let us know if you will be able to join us at the workshop! If you have any question, please contact us at, [email protected]