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INF2-FDS: S1 Week 1 - Introduction and Data

  • Slides
    • FDS-S1-01-1-Welcome-and-intro
    • FDS-S1-02-1-about-data
  • Comprehension Questions: see Learn Ultra for formative questions for both lectures.
  • Lab: INF2-FDS: S1 Week 1 Lab
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  • INF2-FDS: S1 Week 1 Lab

Book traversal links for INF2-FDS: S1 Week 1 - Introduction and Data

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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 1 Lab
    • INF2-FDS: S1 Week 2 - Descriptive statistics
    • INF2-FDS: S1 Week 3 - Exploratory data analysis, data communication and visualisation
    • INF2-FDS: S1 Week 4 - Data Ethics, Data Scraping and statistical relationships
    • INF2-FDS: S1 Week 5 - Introduction to supervised learning - Nearest Neighbours
    • INF2-FDS: S1 Week 6 - Linear models
    • INF2-FDS: S1 Week 7 - Coursework 1
    • INF2-FDS: S1 Week 8 - Multiple regression
    • INF2-FDS: S1 Week 9 - Dealing with high dimensions
    • INF2-FDS: S1 Week 10 - Randomness, sampling and simulation
    • INF2-FDS: S1 Week 11 - Estimation and confidence intervals
    • INF2-FDS: S2 Week 1 - Hypothesis testing and A/B testing
    • INF2-FDS: S2 Week 2 - Logistic regression
    • INF2-FDS: S2 Week 3 - Introduction to unsupervised learning - K-means
    • INF2-FDS: S2 Week 4 - Ethical and legal issues in supervised learning
    • INF2-FDS: S2 Week 5 - Regression and inference
    • INF2-FDS: S2 Week 6 - 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
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