start filling out a little

[kweav]

• Added to the motivation and audience within 01-intro.Rmd
• Added a file 01b-overview.Rmd that incorporates the intro outline as headers
• Added the new file 01b-overview.Rmd to the _bookdown.yml

Are we comfortable using the terms "wet lab" or do we want to switch it out? I know some people aren't comfortable with those terms, but don't know any others that are widely known/easily switchable.

I can make and add an avatar for the intended audience that shows someone with wet lab equipment smiling and then frowning or looking intimidated with a computer?

[github-actions]

No spelling errors! 🎉
Comment updated at 2024-06-21-22:51:39 with changes from 5a810b0

[github-actions]

No broken url errors! 🎉
Comment updated at 2024-06-21-22:51:39 with changes from 5a810b0

[github-actions]

Re-rendered previews from the latest commit:

• 👀 Quick preview of course website here *
• 🔬 Comprehensive download of the course website here
• Download the .docx file

* note not all html features will be properly displayed in the "quick preview" but it will give you a rough idea.

Updated at 2024-06-21 with changes from the latest commit 5a810b0

[kweav]

@carriewright11 edited the files a bit and some slides based off of feedback from yesterday's meeting

Some of the bigger changes since yesterday include

• Made an avatar for audience which is included using ottrpal
• Put "placeholder" slides in where I know they need to go for concepts discussed, etc. But these still need to be developed
• Added the slide for LOs for the overview chapter
• Am trying out a new title for the whole of the overview chapter before those LOs, specifically "The who, what, when, where, and why of Computational Biology": Trying to be a little bit cute, but also think it does a good job of communicating it all -- The idea behind this is that by the end of the chapter I want to communicate that the who is everyone, particularly them/whoever is looking at the course material; the what is what computational biology is/what it can do for their research; the when is now; the where is everywhere throughout biomedical research, but particularly in data wrangling ,visualization, etc. and finally the why is because of all of the benefits and how scientific discovery works with big data and should be reproducible/transparent, etc.