Workshop descriptions and registration
Friday, March 8, 2024
We are pleased to offer an array of complimentary training sessions, each of which is free to attend. Register for one or more training events by completing the by Friday, March 1. Early registration is encouraged, as seats are limited. Upon registration review, you will receive a confirmation email.
Presented by Amazon Web Services (AWS)
provides a comprehensive understanding of building ML use cases. Using SageMaker Studio Inetgrated Development Environment (IDE), participants will learn available feature engineering methods, built-in algorithms and steps for training, tuning and deploying ML models. The workshop guides participants in building their own model and demonstrates a "lift-and-shift" from on-premises machine learning (ML) workloads to Amazon SageMaker. It explores advanced concepts like Model Debugging, Monitoring, AutoML, and offers guidance on evaluating participants’ ML workload with the AWS ML Well-Architected lens. This workshop is accessible to anyone interested in AWS machine learning.
Presented by the Â鶹ӳ» Cybersecurity Center
This workshop on safe data management provides an overview of the importance of handling data securely. Attendees will learn about the dangers of data breaches and how to best protect themselves, especially when working with health data and personally identifiable information. Acting as members of a fictitious research lab, attendees will work together to create a robust Data Safety Plan that shields their groundbreaking research from potential risks.
Presented by the Â鶹ӳ» Bioinformatics Center and Office of Digital Learning
ChatGPT and other generative AI are revolutionizing academia and changing the way we do things. This technology is constantly changing, with new functionality added at an astonishing pace. Come and join a roundtable discussion of what this new technology means for academia. We will cover an introduction to ChatGPT, the ethics of generative AI use, and how chatbots can be used in research and teaching. Bring your ideas, opinions, and experiences for an interesting and informative discussion.
Presented by the Â鶹ӳ» Bioinformatics Center and Pronghorn
Morning session: Introduction to Linux/Unix and HPC
In the first session of our comprehensive workshop, we will guide participants through the essential aspects of Linux/Unix and high-performance computing (HPC). We will cover fundamental concepts and commands that are crucial for participants to understand and navigate effectively within a Linux/Unix environment.
Session highlights:
- Directory structure of a Linux/Unix system
- Anatomy of a Linux command
- Understanding the concept of a shell
- Command line options and TAB completion
- Navigation techniques: Relative vs absolute pathing
- CONDA installation: A tool for user-level program installations
- Working with files using fundamental Linux commands
- Introduction to piping commands
- Covered commands: ls, cd, mkdir, mv, touch, tree, htop, nano, cat, less, wc, grep, rm, rmdir, history
Afternoon session: Utilizing Pronghorn and Interacting with SLURM Job Scheduler
The second half of the day will focus on practical applications, delving into the effective use of Pronghorn and interaction with the SLURM job scheduler while running automated analysis execution.
Session Highlights:
- Working with compressed data
- Utilizing screen commands
- Initiating your first SLURM job
- SLURM interactive session for testing
- Scripting for automated analysis execution
- Converting scripts into SBATCH scripts for Pronghorn
- Transferring data files to/from Pronghorn
- Singularity containers: Rstudio server use case
- Processing multiple samples in parallel with array SBATCH scripts
Presented by Professor Kyra Stull and the Â鶹ӳ» Bioinformatics Center
The R language, along with its amazing collection of libraries, is one of the most powerful tools you can use to tackle data analysis and to generate informative visualizations.
Morning session: Getting started with R programming
Discover the fundamentals of R programming and RStudio in this hands-on workshop, designed for beginners with no prior knowledge. Dive into essential data manipulation, organization, and exploration using base R and tidy format with provided example datasets. Covering R basics, including command line calculations, variable usage, and data structures, the workshop guides participants in loading, accessing, and summarizing data through statistics and plots. This session provides a practical introduction to programming with R, emphasizing its application in data science and research.
Afternoon session: Data visualization with R
This session will teach participants how to display their data appropriately using ggplot2, which is an R package dedicated to data visualization. We will cover visualizations for univariate, bivariate, and multivariate relationships and for both categorical and continuous data. This includes bar plots, histograms, boxplots, line plots, lollipops, scatterplots, bubble plots, correlations, and more.
Presented by Research Data Services (part of University Libraries)
Learn how to easily tackle grant funder requirements for a data sharing and management plan (NIH, NSF, and others by request). This workshop, aimed at faculty and researchers, will help you enhance your data handling skills and ensure your research meets the highest standards. Engage in a step-by-step process to create your DMS through hands-on exercises and gain a set of resources and tools for continuous support in data management planning. Feel free to bring your existing DMS for the peer-review session, offering constructive discussions and refinements.
Presented by the School of Business and Office of Digital Learning
This roundtable session invites undergraduate students to engage in an interactive exploration of the exciting possibilities and challenges presented by artificial intelligence in higher education. Through open discussions and collaborative brainstorming, participants will have the opportunity to share their perspectives on how AI can enrich their learning experiences, address academic needs, and shape the future of undergraduate education. Together, we will delve into real-world examples and potential applications of AI, fostering a student-centered conversation that empowers undergraduates to become active contributors in the advancement of AI technology in higher education.
First hour: Tips and tricks for success
- Facilitated discussion by University faculty and staff on AI applications and advice for practical use for students
- Demonstrations showcasing successful strategies, tools, and prompts
- Sharing of resources, case studies, and best practices for integrating AI in undergraduate learning.
- Q&A sessions for participants
Second hour: Open discussion with students
- A student-led conversation where participants can openly share their experiences with AI
- Opportunities for students to discuss challenges, innovative uses, and personal stories related to AI in education
- Peer-to-peer knowledge exchange and brainstorming sessions
- Encouragement for students to propose new ideas or initiatives involving AI in their educational journey at the University
Presented by IBM
Learn how IBM watsonx unlocks the new potential of AI Assistants powered with generative AI and automation to drive productive employee and customer experiences.
Presented by Professor Theresa McKim in collaboration with the Â鶹ӳ» Bioinformatics Center
Python is a high-level, general-purpose, and open-source programming language. It is emerging as one of the most popular programming languages, both for scientific computing and general use. In this Python crash course, we will cover an overview of Python and programming fundamentals, and then describe how to use Python for data processing, analysis and visualization. At the end of this module, you will be able to:
- Understand the basic components of a Jupyter notebook
- Write and debug basic Python code
- Use functions, loops, conditional statements, and apply programming fundamentals applicable across computing languages
- Analyze a dataset using Python libraries built for data science
- Learn and discuss best practices for data visualization to communicate your results
Are you interested in government service? Federal executive branch roles? Top national positions? Security clearances? Join us for a round table discussion of questions such as:
- How could interested students take the first steps toward government service?
- What is the application process for internships? Full-time positions?
- What should students focus on in their studies to be competitive for these positions?
- What is the polygraph test like? Do I need to take it?
- What is a security clearance?
Curious about AWS cloud computing services? Interested in exploring additional training opportunities or overcoming challenges from past projects? Or if you're unsure where to start your cloud computing journey, join us for an engaging meet and greet with the AWS team!