Berkeley DATA 8: Foundations of Data Science
DATA 8 is Berkeley's intro data science course and one of the largest courses on campus, combining Python programming, statistical inference, and prediction with real datasets in Jupyter notebooks. It assumes no prior programming or statistics and anchors the Data Science major.
Fennie is independent and not affiliated with UC Berkeley. This is an unofficial study guide.
What makes it hard
Individually the pieces are gentle, but the course braids programming and inference together, and students weak in either thread struggle when they combine: bootstrap confidence intervals implemented in code, hypothesis tests you have to program yourself. The exams test conceptual understanding of inference, which surprises students who treated it as a coding class.
What you'll cover
- • Python and the datascience module
- • Tables, visualization, and data manipulation
- • Sampling and empirical distributions
- • Hypothesis testing and A/B testing
- • Bootstrap confidence intervals
- • Regression and prediction
- • Classification basics
The DATA 8 study guide
How to study for Berkeley DATA 8, step by step.
- 1
Keep both threads current every week
DATA 8 braids Python and statistical inference together, and falling behind in either thread breaks the combination. Do the labs and homework the week they're assigned so neither skill goes stale.
- 2
Type the code yourself, never copy-paste
The notebooks make it easy to run cells on autopilot. Retyping and modifying the table operations is how the datascience module syntax becomes yours, which matters when exams ask you to read and write it cold.
- 3
Ask why each inference method works
For the bootstrap, hypothesis tests, and confidence intervals, be able to explain in plain English what the procedure does and what the result claims. Exams grade that conceptual understanding, not code recall.
- 4
Work past exams for the conceptual style
Students who treated DATA 8 as a coding class get surprised at exam time. Past exams from the course site and Berkeley's archives show exactly how inference concepts get tested; work them on paper.
Today
Today's DATA 8 plan
What a Fennie Daily Plan looks like for DATA 8. Yours is built from your own syllabus and adapts every day to your deadlines and progress.
First plan free, no card required. Fennie is independent and unaffiliated with your school.
FAQ
Is DATA 8 hard?
It's one of Berkeley's more accessible technical courses by design, with no prerequisites and a gentle Python ramp. The difficulty shows up at exam time, when questions probe inference concepts. Students who understand why each method works do well; pure code-copiers don't.
Should I take DATA 8 or CS 61A first?
Either order works, and many students take DATA 8 first as a gentler intro to programming before 61A. If you're a prospective Data Science major, DATA 8 is the natural starting point; CS majors often go straight to 61A.
Does DATA 8 count toward the Data Science major?
Yes. It's the foundational course of Berkeley's Data Science major and a prerequisite for DATA 100. It also satisfies requirements or electives in several other majors, which is part of why enrollment is so large.