WEEK 1: Introduction (1 lecture)
Welcome to DS 593! For each week in the course I will give an overview of what we will be discussing in lectures, discussions, and what our expectations are for your work outside of class.
This week's checklist (due Sunday 1/25)
- (Note that there is NO discussion on Tue, Jan 20!)
- Complete entry survey (before the first lecture if possible!)
- Attend Lecture 1 on Wed, Jan 21 and turn-in the syllabus activity on paper
- Create a GitHub account and a GitHub Classroom repo
- Complete Reflection 1, pushed to GitHub
- Complete Lab 0, pushed to GitHub
This week's learning objectives
After Lecture 1 students will be able to...
- Explain the overall course objectives, deliverables, and key policies
- Use the course syllabus, website, and other resources to address most questions that might arise during the course
- Set up a GitHub account and create repos from GitHub Classroom for use during the course
- Select and use a python enviornment for local development (enough for the first two weeks of the course)
- Sign up for Google Colab and test using cloud compute
- Begin using AI tools to aid in set-up troubleshooting
Week 1 Reflection Prompts
- What do you hope to learn?
- If you had unlimited time and resources, what project would you dream of working on for this course?
- What has been one highlight and one lowlight of your language model interactions prior to this course?
Lab 0: GitHub and Google Colab
- Connect your GitHub account to GitHub Classroom and start your private repo
- Add your week 1 reflections to your repo
- Create a python notebook for your repo with some working code (hello world!)
- Set up a Google Colab account / begin to apply for student credits (this isn't graded, but it would be helpful to start now)
- Add three commits and a PR to your repo