MSA Share20 Class of 2022

MSA Share20s are an opportunity for students to present to their classmates about relevant and interesting topics. Students work with Dr. Sarah Egan Warren to prepare their presentations and deliver their talks at lunchtime. The talks last up to 20 minutes with 10 minutes of time for questions. The speakers hone their presentation skills and the participants learn something new (win-win)!

Two members of the class of 2022 delivered the earliest MSA Share:20 of any previous class.


Sam Jasper and Manasa Peddakama provided a brief tutorial called Using Microsoft OneNote and how to use it during the MSA program. Specifically, they discussed downloading a version of OneNote, using the basic structure (folder, section group, section, page), integrating with other MS applications, using OneNote for project management and knowledge sharing, and considering features like embedding audio files and videos, limitations, and strategies.


Alex Pirsos and Lindy Bustabad presented the Top 5 Tips for LinkedIn Networking. Alex and Lindy shared 5 tips you need to know as you start your LinkedIn networking journey, including how to connect with industry leaders, search for alumni, reach the magic 500, send the first message, and continue the connection.

Craig Schmier presented From Idea to Execution: How I Created My Own Game Show. In August 2021, Craig Schmier gathered eight MSA students to test his idea in a Zoom game show he designed called Turncoat. Craig shared how he turned his fascination with reality television into a hobby as he walked through his creative process.


Tim Milowic presented You Worked Hard for Your Money, Now Make Your Money Work for You. In his talk, Tim provided a beginner’s guide to what it takes to retire early, earn passive income, and set yourself up for the future.

Prudvi Gaddam presented Take 10 Minutes Out of Your Day to Do… Absolutely… Nothing. Prudvi shared how medication can help you destress, learn to concentrate, and understand your internal life a little better.

Jon Luettgen presented Turn Your Brain into a Computer. During his interactive session, Jon shared how to estimate an answer, square any number ending in 5, multiply any two-digit number, and add from the left.

Jackson de Oliveira presented Flashcard Quiz: Leveraging JavaScript for Heavy Lifting. Jackson broke down the JS flashcard quiz he created. In addition, he discussed JavaScript and its relationship in web technologies and how it might help the work of data scientists.

Louise Lindegaard presented Mapping in Data Science: How to Use Maps to Level Up Your Data Science Skills. Louise talked about how we see maps everywhere for a reason. Maps are one of the most accessible and flexible visualization tools you can use to communicate virtually any type of information. She discussed how you can use beautiful and informative maps to emphasize any insight or complement any analysis. And she encouraged her classmates to learn how to add geospatial analytics to their data science toolbox.

Katie Forester presented Failing Forward: Learn How to Use Design Thinking to Shift Your Mindset. In her interactive talk, Katie introduced the concept of design thinking that was created by Stanford’s as a human-centered, iterative process that can be used to tackle problems and to see failures as motivators. Katie demonstrated (with the help of audience participation) how to apply the design thinking process to practicum teams, homework problems, relationships, and life in general.

Jackson de Oliveira, Robert Seybold, and Sam Jasper presented One Data Science Flowchart to Rule Them All. Have you ever thought through all the steps required for <insert data science concept here> and wondered what R/Python code would be required to complete each of those steps? Jackson, Robert, and Sam Jasper unveiled the first phase of their project to help you (help yourself) through these steps. During this Share20, they discussed how this resource (an RBookdown document with a flowchart for each topic and associated code for each step) can be used to solve an example linear regression problem quickly and effectively.