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