Lecture 0 Notes

Goals

• Have a high-level view of what Data Science is about and what data scientists do
• Get a high-level sense of the steps of the “data science life cycle”
• Begin thinking about how to ask questions that can be answered with data.
• Contemplate the context of data science in today’s world and in the AI-enabled [u,dys]topian future

Intro and Logistics

• [slides] Welcome; about me
• [slides] Plan for today
• [slides / webpage] Logistics
  • Webpage/syllabus
    • Schedule table (flexibility)
    • Major assessment items / cadence

What is data science? What is data?

• [ws/wb] What is data science? Student suggestions
  • my take: The process and/or study of extracting insights from data.
  • premise: “Data is not information is not understanding is not wisdom” - Clifford Stoll
  • Tools: CS, Stats, Domain expertise
  • Practitioners: CS, Stats, Business
• [ws/wb] What do data scientists do? Student suggestions
  • answer questions
  • discover patterns, trends, insights
  • make predictions (classification, regression)
• “The Data Science Life Cycle”:
  • Collection
  • Cleaning
  • Exploration
  • Modeling
  • Interpretation
• [ws/wb] What is data? Student suggestions

Why are you taking this class? What are we doing here?

The world is on fire in various ways and AI is changing everything (for better or worse). What is the role of data science in today’s world? What is the role of data science in the AI-enabled [u,dys]topian future?