NCCS Internship Resources

Schedule

Team Presentation Schedule

• mon 6/27: olivia
• tues 6/28: none
• wed 6/29: (no standup)
• thurs 6/30: blake & vincent
• mon 7/4: holiday: no standup
• tues 7/5: akila & pat
• wed 7/6: su & christian
• thurs 7/7: none

Instructions:

The goal of the presentation is to move your project forward by getting feedback from teammates, seeking advice on current problems, and offering opportunities to learn from each other by seeing examples of code and hearing people think through problems out loud.

The audience for your presentation is teammates, so you don’t have to sell your project. Rather, you are selling your PROCESS to other experts in the room.

You might start with the end goal and work backwards. Here is what I want (final dataset, example visualization our model output), here is how I am trying to get there (process model of the steps needed). This type of high-level context helps prime productive conversations wtih the team.

Make the meeting actionable. What is one problem you need to solve, one decision you need to make, or one type of feedback that would help move the project forward at this stage?

Good things to highlight are the logic of a specific problem you are trying to solve, some code that is currently not working, an engineering question where you need to make a decision that involves trade-offs.

Slides are always welcome, but keep background context to a minimum (people are familiar with your projects already). Instead focus on explaining your mental model of the project, and how that shapes your implementation strategy.

Suggestions:

• Conceptual diagrams of your code are helpful - functions are called in what order and why? What are they doing at each step?
• Pick one or two things for a drill-down into details on code or data.
  • You can’t do this with your entire project in 20 minutes, so pick one code snipped, one function, or one algorithm to highlight.
• Reproducible examples are always welcome!
  • Make demo datasets accessible using dput() functions to embed R objects within a script, or loading the demo dataset to GitHub and providing code to load it remotely.
  • Share links to your code and data so others can follow along.
  • Create a script so people can load the package, load demo data, and follow-along.

The goal is to get feedback on your current work, but also for teammates to get a window into projects, learn from seeing how others are implementing their code, and have an opportunity to hear others talk through problems out loud.