Milestone map
Milestone map
2 milestones
Do the course work in public
4–8 weeks (1–2 hrs/week)
Take Data Science: Wrangling for free and do the exercises in the book's wrangling chapters (importing, reshaping, joining, strings, dates). Keep everything in one public repo or notebook as you go. OSSU links the edX page; we link the course author's free book, which has the same lessons and exercises.
Proof required
Link your public repo or notebook with the exercises in the book's wrangling chapters (importing, reshaping, joining, strings, dates), and a screenshot or log showing the self-check passed.
What gets checked
- Each exercise runs and gives the right table.
- Joins keep the rows they should (counts shown).
- Messy values are fixed with code, not by hand.
Common mistakes
- Copying posted answers: verifiers read the history.
- Skipping the self-check, then asking for review too early.
Powstik Guide
A public repo or notebook with the exercises in the book's wrangling chapters (importing, reshaping, joining, strings, dates).
Steps
- Make a public repo or notebook first.
- Do one unit at a time and commit after each.
- Run the self-check: Do the Data Cleaning exercises; Kaggle checks each answer.
- Write a short README: what is here and how to run it.
- Ask three people who know the topic to check it.
Template
README Course: Data Science: Wrangling (Introduction to Data Science by Rafael Irizarry (free book; the course's own text)) What is here: How to run it: Self-check result: What was hardest:
What gets sent back
- No history, just one big upload.
- Self-check not shown.
- Code that does not run from the README.
Resources
Foundationstart here
Depthgo deeper
What a verifier looks for
- Each exercise runs and gives the right table.
- Joins keep the rows they should (counts shown).
- Messy values are fixed with code, not by hand.
- Ask one question about a choice in the code; the answer should be clear.
You'll sign in first, then come straight back here.
Clean a messy public dataset
1–3 weeks (5–8 hrs/week)
Use what you learned. Make a script that turns a messy public dataset into a tidy table, with a short note of every fix. Keep it small enough to finish in about two weeks.
Proof required
Link a script that turns a messy public dataset into a tidy table, with a short note of every fix, with a README that says how to run or read it.
What gets checked
- Rerunning the script gives the same table.
- Every fix is listed with a reason.
- Row counts before and after are shown.
Common mistakes
- A project too big to finish.
- A demo that only works on your machine.
Powstik Guide
A script that turns a messy public dataset into a tidy table, with a short note of every fix.
Steps
- Write one line: what it does and for whom.
- Build the smallest version that works.
- Test it on someone else's machine or with someone else reading it.
- Write the README.
- Ask three people to check it.
Template
README What it does: Who it is for: How to run it: What I would do next:
What gets sent back
- Does not run from the README.
- Not clearly the person's own work.
- Claims more than it does.
Resources
Foundationstart here
Depthgo deeper
What a verifier looks for
- Rerunning the script gives the same table.
- Every fix is listed with a reason.
- Row counts before and after are shown.
- Check that the work is the person's own.
You'll sign in first, then come straight back here.