Data Science Workshop

Track: Workshop (Full Day)
Skill Level: Intermediate
Room: WS Room A312
Time Slot: Mon 2/15, 9:00 AM
Tags: data , data science , r programming language , d3 , big data

This course will introduce you to the various skills that go into data science, provide practical walkthroughs of relevant languages and tools and lay down a study plan for moving forward in this field.

As there is a rush to hire data scientists these days, there is a coincident rush to update resumes to include the term “Data Scientist”. Unfortunately, like most types of science, it is less a single topic and more a multi-disciplinary way of thinking, inquiring and communicating.

You won’t become a data scientist over night, but you can learn to be one in time. Individuals do not need to know everything about the field, but teams should be composed of individuals who collectively do.

We will cover:

  • Data Science as a field
  • Basic statistics and numerical methods for dealing with data
  • Doing Data Analysis in Spreadsheets
  • The R programming language, its environment and online ecosystem
  • R’s visualization packages
  • Interacting and visualizing data with D3.js
  • Interacting with Big Data environments in R
  • Interacting with Linked Data in R
Brian Sletten

Brian Sletten is a liberal arts-educated software engineer with a focus on forward-leaning technologies. His experience has spanned many industries including retail, banking, online games, defense, finance, hospitality and health care. He has a B.S. in Computer Science from the College of William and Mary and lives in Auburn, CA. He focuses on web architecture, resource-oriented computing, social networking, the Semantic Web, data science, 3D graphics, visualization, scalable systems, security consulting and other technologies of the late 20th and early 21st Centuries. He is also a rabid reader, devoted foodie and has excellent taste in music. If pressed, he might tell you about his International Pop Recording career.