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  2. INF2-FDS: Informatics 2 - Foundations of Data Science
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  4. INF2-FDS: S1 Week 4 - Data Ethics, Data Scraping and statistical relationships

INF2-FDS: Task: Preparation for S1 Week 5 Workshop

The aim of the S1 Week 5 workshop and the associated preparation is to help you achieve the learning outcomes:

  1. Describe and apply good practices for storing, manipulating, summarising and visualising data.
  2. Use standard packages and tools for data analysis and describing this analysis, such as Python and LaTeX.

These learning outcomes will be assessed in Coursework 1, released at the start of Week 6.

Full instructions for preparation are in this document:

Document
FDS-S1-05-visualisation-1-prep.pdf (242.92 KB)

You will need to use these documents, which are referred to in the instructions:

Document
FDS-visualisation-principles-handout.pdf (74.95 KB)
Document
FDS-S1-05-visualisation-2-mark-sheet-individual_1.xlsx (16.69 KB)

 

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All rights reserved The University of Edinburgh

Book traversal links for INF2-FDS: Task: Preparation for S1 Week 5 Workshop

  • INF2-FDS: S1 Week 4 - Data Ethics, Data Scraping and statistical relationships
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  • INF2-FDS: S1 Week 4 Lab

Navigation links

  • 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
    • 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: Task: Preparation for S1 Week 5 Workshop
      • INF2-FDS: S1 Week 4 Lab
    • 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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