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Welcome to the Residential MSDS Technical Orientation

GOAL: Your goal is to complete the technical orientation checklist before the start of classes.

  • N.B. The majority of work is done independently
  • N.B. Classes start June 17 (you have the weekend).

Schedule

Date Place Time Activity Evening Materials
Thursday, June 13, 2024 Data Science, Room 305 13:00-17:00 orientation homework slides
Friday, June 14, 2024 Data Science, Room 205 13:00-17:00 orientation homework slides
Saturday, June 15, 2024 n/a 4 hours homework homework
Sunday, June 16, 2024 n/a 4 hours homework homework
Monday, June 17, 2024 Data Science, Room 305 09:00-11:15 class homework
Tuesday, June 18, 2024 Data Science, Room 305 & 205 09:00-11:15, 13:00-15:45 class homework
  • "The great thing about weekends in gradschool is that you don't have to go to class before starting your homework"

The Checklist

You may complete these items in any order

  1. watch Jurassic Park (link to free access via uva library)

    • Explain two ethical challenges the characters in the movie face and what you would do in their place.
    • Discuss with a member of your cohort: strategies for identifying ethical challenges in the digital world.

  2. complete computer hardware survey - link

  3. read Code Review Guidelines for Humans

    • Commit to ...
      • being humble.
      • asking if someone wants to recieve feedback before giving feedback (Sometimes, people just need you to listen to them).
    • Select one principle from this article and share it with a member of your cohort. Tell them why it resonated with you and what you will do to keep it in your mind.

  4. Make your main orientation deliverable

    Our main deliverable is a slideshow that serves as a facebook for our cohort. We will use the data from the computer survey.

    • explore the data - link
    • make a histogram - using the tools you have learned over the orientation make a histogram representing the information contained in our dataset
    • create your slide in the presentation - link
      • Your Name
      • A picture of you showing some part of your life/personality that isn't related to data science
      • Your histogram
      • Link to the github repo with the code for making your histogram

  5. call someone you should call more often and tell them about what you are excited to learn this summer

  6. complete the following 4 badges:

    You may work on these badges in any order and simultaneously. If you would prefer to go sequentially starting from first principles the recommended order is: GitHub --> VSCode --> Python.

Badge Link Logo
GitHub link
VSCode link
Python link
R/Rstudio link

  1. Summer Professor's Special Requests. There are items your upcoming professors have asked you to pay particular attention to. (* indicates difficulty)

    Think of this section as a test. When you read this list ask yourself if you are prepared to teach each item to someone.

    • Professor Kropko
      • pip / pip install [***] (python badge)
      • you must test, don't just assume it works (e.g. run import numpy afterwards to see if it is working) [*]
      • Notebooks [*] (jupyter badge)
    • Professor Alvarado
      • The git/github ecosystem and how it relates to files on the cloud and your laptop [**] (github badge)
      • CLI [**] (VSCode badge)
      • Local v Remote [**] (VSCode badge)
      • PATH/working directory (aka Where's my file) [**] (VSCode badge)
      • Clear understanding of the python install [***] (python badge)
      • Notebooks [*] (jupyter badge)
    • Professor Afriyie - The R Badge [*]

Schedule

This orientation takes place over two days. The main modality is the mini-lecture followed by working period. During the working period the instructors move about the room and coach students individually or in small groups.

Day Activity Topic
Day 1 Kick off The Inner Game of Data Science
Mini-Lecture GitHub
Mini-Lecture VS Code
Mini-Lecture The checklist
Wrap Up HW Goal
---------------------- ---------- ---------------
Day 2 Warm Up What If?
Mini-Lecture Python
Mini-Lecture R/RStudio
Mini-Lecture Make Class Facebook
Finale Present Facebook

Recommended Reference Resources

Programming

Deep Cuts

For when you want to kick back and watch some content

How to submit feedback

I love getting feedback. Here is the preferred way to submit it.

  1. Fork this repo
  2. Work on your fork to make improvements
  3. Issue a pull request

Alternatively you can submit feedback by creating an issue on the repository.

What's Next

Class Name Professor
DS 5100 Programming for Data Science Rafael Alvarado
DS 6001 Practice and App of Data Science Jonathan Kropko
STAT 6021 Linear Models for Data Science Prince Afriyie

Professor Alonzi will also be hosting monthly workshops on topics like Cloud Computing.

#ToDo

  • add section about documentation and why not ChatGPT (also push to online an phd
  • add bash (see email Royal Collins, Sadie (smr2h) on Note for next MSDS Res Bootcamp on 7/10)