DataScience

What would a course on Data Science look like?

Introduction

Drew Conway's Venn diagram of data science

Topics would include

• What is relevant for the UoB?
• y=f(x) relationships:- classifiers & regression
  • Examples: Linear & logistic regression, K-Nearest Neighbours, Decision Trees, Neural Networks etc.
• Data topics:
  • Training, Test & validation data.
  • Sources of data, e.g. web scraping.
  • Exploratory Data Analysis (EDA).
  • Cleaning & munging data (90% of your effort?). Useful Linux tools.
  • Feature selection.
• Model selection & training topics:
  • Algorithms that scale.
  • Supervised vs. Unsupervised training.
  • Overfitting.
  • The curse of dimensionality.
• Programming Skills:
  • "Clean code shows clarity of mind,"
  • Languages: R? Python? Others?
  • Version control.
  • Build systems.
  • Testing.
  • Scripting and automation.