Course outline
The full outline: what we do each week, the readings, how the assessment works, and the policy on using AI in your submissions. Read the assessment section before the first quiz.
Open →Start here
What the course covers, and how it is gradedAssignment results
Final · 18 September 2026Final assignment leaderboard
Final participation and quality scores, with marks for each assignment and the scoring rules. Miraya and Pallavi share first place; Srihasini is third.
View results →Try it yourself
Explore and experimentwordmath: arithmetic with meaning
What happens when you calculate king − man + woman? Try your own words and phrases, compare the closest matches, and inspect the numbers behind the calculation.
Open wordmath →Topics we have covered
One page per topic. More each weekData project ideas
Starting points for choosing a question and a workable dataset, with links to official sources, public mirrors, and data explorers. Also available as a printable PDF.
Open →Summary statistics, and when they lie
Mean, median, mode, range, IQR and standard deviation. What each one means, when it is the right one to report, and the five ways a correctly computed summary can still tell a false story.
Open →Could this just be luck?
The null hypothesis and the p-value, worked out from the bus-company question in the first quiz. What "statistically significant" does and does not mean, and why sample size changes everything.
Open →Principles of data visualization
What makes a chart good: starting from a question, making the right comparison easy to see, graphical integrity, and showing uncertainty instead of hiding it.
Open →Also here
Not part of the weekly sequenceRegression activities
Straight-line regression, classification, logistic regression, and gradient descent, done by hand before any library.
Open →GenWise 2026 material
The resource index from the first run of this course, at GenWise in June 2026. We cover much of the same ground in a different order, so treat it as extra reading rather than as the syllabus.
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