Introduction

Hello

  • Adriana Picoral (PhD, you can call me Adriana)
  • picorala@montclair.edu
  • Office: Schmitt 374
  • Office hours: Tuesdays and Thursdays, 1:45pm to 3:30pm

Active Learning

  • I expect you to actively participate in class (that does not mean you have to speak to the entire group)
  • Lots of hands-on activities and discussions
  • We will be using Gradescope (more on this later) to submit in-class work and for homework assignments

Ice Breaker

  • Find at least one person to talk to.

  • Introduce yourself (name, major/program, anything else you’d like to share)

  • What is something you are good at and that took many hours of practice?

Course Overview

  • Introduction to advanced techniques in Data Science
  • Focus on both concepts and examples
  • Focus on hands-on, bring a laptop to class if you have one
  • Focus on real data in assignments

Course Overview

What is missing in this image?

Course Overview

Topics:

  • Review the cycle of data science: data wrangling, and visualization
  • Major topics: how to make data-driven inferences and decisions by using fundamental techniques in machine learning and neural networks

Coding tools