Information is beautiful, when presented well. This course has three themes:

Theme 1: Design --- How should we think about information presentation? How can information be presented for best impact & understanding?

Theme 2: Data Science --- What are the most important data science tools and skills that every college graduate should have?

Theme 3: Discovery --- We will apply our newly acquired data science skills to both historically important as well are currently cutting edge data problems to re-discover and discover new results (and we will focus on how the presentation of the results is an important part of the discovery & understanding process). 

Topics touched on in the course:

Methods and strategies for impactful information presentation;

History of Information Presentation and Museum Design;

Interpretive Design and Visual Storytelling;

Celtic Symbols and Icons (including Troubled Symbols);

Introduction to the Computational Beauty of Nature;

Self-Similarity and Fractals;

Matrices and Matrix Computations;

L-Systems & Natural Design;

Introduction to Python;

Self-Organized Systems & Emergent Design;

Data and Computational Journalism;

Introduction to Probability and Statistics;

Random Variables and Dependence;

Conditional Probability and Bayes Theorem;

Law of Large Numbers & The Central Limit Theorem;

Estimation, Confidence Intervals & The Student-t Distribution;

Regression;

Clustering & Unsupervised Learning;

Dimensionality Reduction;

Neural Networks and Deep Learning;

Epic Visualizations (e.g., The Work of Edward Tufte);

Visualizing Data in Python;

Building Dashboards in Dash

Stories of Discovery:

  • How to Brew Better Beer Using Math
  • What is Life & How Schrodinger Inspired Watson & Crick
  • How Saliva is Used to Determine your Irish Ancestors
  • Rock Formations and Oil Discovery
  • Geoffery Dean: Ireland’s First Medical Data Scientist
  • How a Drop of an Expectant Mother's Blood can save her Pregnancy