INF2-FDS: S1 Week 1 - Introduction and Data
- Slides
- Comprehension Questions: see Learn Ultra for formative questions for both lectures.
- Lab: INF2-FDS: S1 Week 1 Lab
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- INF2-FDS: Course team
- INF2-FDS: Schedule
-
INF2-FDS: Course Materials
- INF2-FDS: S1 Week 1 - Introduction and Data
- INF2-FDS: S1 Week 2 - Descriptive statistics and introduction to data ethics
- INF2-FDS: S1 Week 3 - Exploratory data analysis, data communication and visualisation
- INF2-FDS: S1 Week 4 - Data Scraping and statistical relationships
- INF2-FDS: S1 Week 5 - Linear regression
- INF2-FDS: S1 Week 6 - Coursework 1
- INF2-FDS: S1 Week 7 - Multiple regression
- INF2-FDS: S1 Week 8 - Dealing with high dimensions
- INF2-FDS: S1 Week 9 - Introduction to supervised learning - Nearest Neighbours
- INF2-FDS: S1 Week 10 - Introduction to unsupervised learning - K-means
- INF2-FDS: S2 Week 1 - Randomness, sampling and simulation
- INF2-FDS: S2 Week 2 - Estimation and confidence intervals
- INF2-FDS: S2 Week 3 - Hypothesis testing and A/B testing
- INF2-FDS: S2 Week 4 - Logistic regression
- INF2-FDS: S2 Week 5 - Regression and inference
- INF2-FDS: S2 Week 6 - Ethical and legal issues in supervised learning and software engineering for data science
- INF2-FDS: S2 Week 8 Project writing workshop
- INF2-FDS: Revision
- INF2-FDS: Labs
- INF2-FDS: Workshops
- INF2-FDS: Resource List
- INF2-FDS: Assessment