Fall 2016 Computer Science 458 Introduction

• Biography. Hybrid: academia (theory) / industry (practice).
  • Yale undergraduate. music major.
  • Developed computer systems for presidential campaigns and the White House.
  • Yale graduate student, M.S., Ph.D., computer science (artificial intelligence)
  • Yale Computer Science Department: Assistant Chairman, Assistant Director of the Yale AI Project, Lecturer.
  • NYU Stern School of Business, Department of Information Systems, Assistant Professor.
  • Wrote three books (T/Scheme, LISP, decision making)
  • Developed investment and risk technology systems for Wall Street. Sell side (Morgan Stanley), Buy side (INVESCO, Bank of America, Commonfund)
• Syllabus
• Guest speakers.
• AWS (Amazon Web Services)
• Modern Portfolio Theory.
• Complete the online student information sheet.
• Python question: what is a lambda list comprehension?
• What's the deal with R and Python? This is not a course in programming languages. The topic of the course is decision systems. Think of it like a literature course in which you read Proust in French. You are expected to know French. However, learning R and Python is not strictly like learning French. Assuming you learned to drive in a Honda, learning to drive another make of car, say a Ford or BMW, is not that steep a learning curve.
• Assignment 0 This problem set gives you the chance to judge the first derivative of said learning curve.
• One more thing. Many of the assignments will involve statistics and finance. We do not expect you to know statistics and finance or economics. After all, this is a computer science course. We will spoon feed that information.
• For discussion in next class: draft reasons for and against each of the following:
  • Getting a tattoo.
  • Voting for each of the presidential candidates.
  We assume that you have relationships with a variety of people: family, friends, colleagues, classmates, etc. Also discuss who among them will be affected by your choice, either positively or negatively.
• Introduction to Decision Making