DS 227 · Syllabus
Knowledge Discovery in Data
Frameworks and processes of knowledge discovery in data, scraping, preprocessing, exploration, storytelling, and ethics
This syllabus is not final. It is a working outline and will change
before the term settles — the topic sequence below is indicative, and grading,
deadlines and course policies are still being finalised. Anything here may be revised
and announced in class. Do not treat it as the official course document.
Topics by week
| Week | Topic | |
|---|---|---|
| 1 | Introduction to Knowledge Discovery in Data | slides |
| 2 | KDD Frameworks: CRISP-DM, SEMMA & the KDD Process | slides |
| 3 | Data Scraping I: Web Fundamentals & HTML Parsing | slides |
| 4 | Data Scraping II: APIs, Dynamic Pages & Scraping Ethics | slides |
| 5 | Data Preprocessing I: Cleaning, Missing Data & Outliers | slides |
| 6 | Data Preprocessing II: Integration, Transformation & Reduction | slides |
| 7 | Data Exploration I: Descriptive Statistics & Univariate EDA | slides |
| 8 | Data Exploration II: Multivariate EDA & Visualization | slides |
| 9 | Data Journalism: Finding Stories in Data | slides |
| 10 | Data Storytelling: Narrative, Dashboards & Communication | slides |
| 11 | Ethics & Privacy in Data and Analytics | slides |
| 12 | Course Synthesis & Final Presentations | slides |
Labs
| Week | Lab | |
|---|---|---|
| 1 | Welcome Lab: Where You're Starting From | Open lab |
| 2 | Walking a Dataset Through CRISP-DM | Open lab |
| 3 | Parsing HTML with BeautifulSoup | Open lab |
| 4 | Pulling Data from an API | Open lab |
| 5 | Missing Values & Outliers | Open lab |
| 6 | Integrating & Reducing Data | Open lab |
| 7 | Descriptive Statistics & Univariate EDA | Open lab |
| 8 | Multivariate EDA & Visualization | Open lab |
| 9 | Finding a Story in Data | Open lab |
| 10 | Building a Narrative Dashboard | Open lab |
| 11 | Auditing a Dataset for Privacy Risk | Open lab |
| 12 | Final Project Workbench | Open lab |
Assessment
Not finalised. The weighting of labs, project and any exams will be confirmed and announced before it affects any submitted work.
Course policies
Attendance, late work, academic integrity and use of AI tools are still being finalised for this term.
Where things live
| Slides & materials | This portal — they stay up all term |
| Course introduction | Welcome deck |
| Lab notebooks | njpinton/ds227-labs |
| Submitting labs | Sign in with your student number, then upload from the lab page |