Upcoming Events

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. Registration: https://dlab.berkeley.edu/cas?destination=/events/r-data-visualization/2023-04-04 Workshop Materials: https://github.com/dlab-berkeley/R-Data-Visualization Software Requirements: Installation Instructions for R and RStudio Is RStudio 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.

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 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. Registration: https://dlab.berkeley.edu/cas?destination=/events/python-deep-learning-parts-1-2/2023-04-11 Workshop Materials: https://github.com/dlab-berkeley/Python-Deep-Learning

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. Registration: https://dlab.berkeley.edu/cas?destination=/events/r-data-visualization/2023-04-11 Workshop Materials: https://github.com/dlab-berkeley/R-Data-Visualization(link is external) Software Requirements:Installation Instructions(link is external) for R and RStudio Is RStudio Not working on your laptop?Attend the workshop anyway, we can provide you with a cloud-based solution(link is external) until you figure out the problems with your local installation.

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. Registration: https://dlab.berkeley.edu/events/python-machine-learning-fundamentals-parts-1-2/2023-04-05 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.

New faculty members commonly describe: Working long hours but making little progress on their research and writing A sense of loneliness that stems from limited mentoring and community Feeling unsupported in their desire for work-family balance and without the skills to achieve it Wondering whether the academic path is the right career choice This webinar is specifically designed to address these issues and provide participants with concrete skills to successfully transition from graduate student to professor. Specifically, participants will learn: The three biggest mistakes that new faculty make in managing their time Why and how to align work time with institutional and personal priorities How to create time for academic writing and research How to organize a network of support and accountability for writing productivity and balance Register for this event here. Activate your your free institutional membership here.

Learning to network to advance your career can be a daunting task. If you would like to learn more about developing career networks and planning for your networking journey, consider attending the “Networking for Career Exploration and Preparation” workshop offered by GradPro and the Career Center. In this workshop, we will discuss how to identify career networks inside and outside academia, the process of conducting informational interviews, and key insights on value-driven career exploration.The workshop will take place on Thursday, April 13th, from 1-2:30 p.m. Please register for the workshop using this link. GradPro Networking Workshop_Flyer

Learning to network to advance your career can be a daunting task. This workshop will offer key insights on how to identify career networks, conduct informational interviews, and how to make a plan to get started on your networking journey. All UC Berkeley graduate students are welcome to attend. The registration form will close at 11:59pm on Wednesday, April 12. The Zoom link for the event will be available upon registration. For questions or any disability-related accommodations, please contact Haripriya Sathyanarayanan at [email protected]. For more information about GradPro, go to: https://grad.berkeley.edu/professional-development.

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.

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 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. Registration: https://dlab.berkeley.edu/cas?destination=/events/python-deep-learning-parts-1-2/2023-04-11 Workshop Materials: https://github.com/dlab-berkeley/Python-Deep-Learning

This workshop introduces the basic concepts of Deep Learning — the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels. You will use the R interface to Keras to become familiar with basic concepts like input and output layers, batch sizes and output dimensions, dropout rates, weight parametrization and bias, backpropagation, and loss, activation, and optimization functions. You will also gain confidence exploring more complex approaches that utilize pretrained and fine-tuned models. Register: https://dlab.berkeley.edu/events/r-deep-learning-parts-1-2/2023-04-19 Prerequisites: D-Lab's Intro to Machine Learning in R workshop series or equivalent introductory machine learning knowledge. Workshop Materials: https://github.com/dlab-berkeley/R-Deep-Learning(link is external) Software Requirements:Installation Instructions(link is external) for R and RStudio Is RStudio Not working on your laptop?Attend the workshop anyway, we can provide you with a cloud-based solution(link is external) until you figure out the problems with your local installation.

Join us for the Map Mashup event kickoff and OpenGeo Lightning Talks, including choosing a map, cartography, georeferencing, open source tools, open data and more! Beverages & snacks will be provided. REGISTER in advance to receive a Zoom link for this hybrid event. Location: Earth Sciences & Map Library Seminar Room (55A McCone Hall) & Zoom This event is part of Map Mashup, a two-day map-making extravaganza. Anyone is welcome to participate in this event, even if you do not plan on submitting a Map Mashup creation. The UC Berkeley Earth Sciences & Map Library invites students and others to use maps from our collection as the basis for a new map that they create. Over the course of two days we're hosting a series of map-related workshops and open work hours for people to work on their maps, either individually or in groups. The map mashups can be created on a computer or using physical materials. We'll publish digital versions of the final map mashups online!

This webinar will feature panelists who have explored a range of career pathways after completing their doctoral studies in languages and literature. Speakers will share stories about their work along with strategies for negotiating different job markets. Topics will include finding careers outside the academy, using transferable skills from your doctoral training, and navigating distinct job sectors. Together the panelists offer visions of multiple career journeys in higher education administration, nonprofit and for-profit organizations, pedagogical design, publishing, and other areas. Register here.

GRAD MAPPING WORKSHOP: PLANNING YOUR SUMMER Facilitated by: Haripriya Sathyanarayanan (Professional Development Liaison), Martha Ortega Mendoza (Professional Development Liaison), and Debra Behrens (Ph.D. Career Counselor) Presented by: GradPro and Career Center Format: Virtual Workshop on Zoom Thursday, April, 20th, 2023 at 3:00-4:30 pm PT (Online) Registration Form   Get a head start on your summer 2023 by beginning to plan out your summer goals. In this workshop you will have the opportunity to reflect on your values and prioritize your personal and professional goals. You will also learn from the Career Center and GradPro about resources and tools to help you to prepare for, stay accountable to, and accomplish your summer goals. All UC Berkeley graduate students and postdoctoral fellows are welcome to attend. The registration form will close at 11:59pm on Wednesday, April 19. The Zoom link for the event will be available upon registration. For questions or any disability-related accommodations, please contact Haripriya Sathyanarayanan at [email protected].

The D-Lab is seeking applications for the 2023-2024 cohort of Data Science Fellows. This infosession will give you an in-depth look at the D-Lab Data Science Fellowship and an opportunity for you to ask questions about the program that may be helpful to your application process to become a Fellow! The Fellowship is designed to give outstanding UC Berkeley graduate students the opportunity to advance their data science training within the D-Lab’s diverse and intellectually vibrant community. Data Science Fellows receive a stipend. After you register you will receive a calendar invitation with the Zoom link.

Learn about the role teaching plays in applying for faculty positions and how to prepare for this aspect of the academic job search from graduate students who have accepted positions at a variety of colleges and universities. Panelists Ty Blakeney French Joining the Faculty at Northwestern University   Marianne Brasil Integrative Biology Postdoctoral Fellow, UC Berkeley Joining the Faculty at Western Washington University   Angela Castillo Anthropology Joining the Faculty at Pitzer College   Jeehyun Choi English Joining the Faculty at Rutgers University   Rockford Sison Mathematics Visiting Assistant Professor, University of Cincinnati Joining the Faculty at Spelman College

This month, the Bay Area Open Science group will be joined by members of the Fraser lab at UCSF. James Fraser, Roberto Diaz, and Christian Macdonald will join us in a conversation about how they incorporate open science values into their bioengineering research, and how they think about getting credit for this work. The Bay Area Open Science Group is a growing community for Bay Area academics and researchers interested in incorporating open science into their research, teaching, and learning. Targeting students, faculty, and staff at UCSF, Berkeley, and Stanford, the goal of the community is to increase awareness of and engagement with all things open science, including open access articles, open research data, open source software, and open educational resources. Through this work the group hopes to connect researchers with tools they can use to make the products and process of science more equitable and reproducible.

Explore career paths outside the United States! This informal conversation over Zoom allows students/postdocs to learn about hiring practices beyond the USA. Yansong Miao, PhD, Associate Professor and Assistant Chair (Internationalization), School of Biological Sciences and Principal Investigator: Institute for Digital Molecular Analytics and Science (IDMxS) at Nanyang Technological University, Singapore (former Berkeley postdoc). Register for this event here.

Looking to bolster your public speaking skills? Look no further than Berkley's own International Toastmasters chapter! Meeting via zoom every Tuesday from 6:15pm-7:30pm, Toast of Berkeley offers a plethora of ways to improve upon your confidence and effectiveness as a public speaker/leader through the support of your peers. Students of all backgrounds and public speaking abilities welcome, no experience required!

This workshop introduces the basic concepts of Deep Learning — the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels. You will use the R interface to Keras to become familiar with basic concepts like input and output layers, batch sizes and output dimensions, dropout rates, weight parametrization and bias, backpropagation, and loss, activation, and optimization functions. You will also gain confidence exploring more complex approaches that utilize pretrained and fine-tuned models. Register: https://dlab.berkeley.edu/events/r-deep-learning-parts-1-2/2023-04-19 Prerequisites: D-Lab's Intro to Machine Learning in R workshop series or equivalent introductory machine learning knowledge. Workshop Materials: https://github.com/dlab-berkeley/R-Deep-Learning(link is external) Software Requirements:Installation Instructions(link is external) for R and RStudio Is RStudio Not working on your laptop?Attend the workshop anyway, we can provide you with a cloud-based solution(link is external) until you figure out the problems with your local installation.

Explore career paths outside the United States! This informal conversation over Zoom allows students/postdocs to learn about hiring practices beyond the USA. Eva Maria Schmid, PhD, Head of Scientific Training, Vienna Biocenter Register for this event here.

Good news! There are powerful tools to manage your level of career-related stress! Having trouble mustering up the energy to retool resumes, cover letters, and linkedin profiles? Becoming discouraged with endless applications, interviews, and email let downs? We have just the program for you. Career Services for Students with Disabilities is partnering with Dinorah Meyer, Career Counselor serving College of Environmental Design and specialist in yoga and mindfulness practice to offer up strategies in managing career readiness stress. Register for this event on Handshake.