Introductory Seminars for First-Year Students

Data-Driven Decisions and Discovery

CS 46N

"Data is the oil of the 21st century"—it's the raw material that today's economies and societies increasingly rely on, though to be useful it must first be extracted, refined, and distributed. The analogy only goes so far, but there is no question that the use of data to drive decisions and discoveries has increased dramatically over the past two decades, thanks to prevalent data collection, cheaper storage, faster computers, and sophisticated new algorithms.

The seminar will have three interwoven components:

  1. Hands-on instruction in tools and techniques for working with data, from spreadsheets to data visualization systems to machine learning packages. Even with no previous programming experience, students will become equipped to perform surprisingly sophisticated analyses and visualizations. Students will complete short assignments on a variety of provided datasets and will propose and undertake a larger project using a dataset of personal interest.
  2. A suite of case studies where data has been key to decision-making or discovery. These studies will be drawn from a wide variety of domains—from social sciences to natural sciences to law, medicine, and politics. Additionally, each student will present a mini-case-study in an area of personal interest.
  3. Ethical issues, including privacy in data collection and use, and the effect of bias in data-driven decision making. We will also discuss how to evaluate claims about data-driven results and recommendations.

Class time will include some lecture-style material and student presentations, along with plenty of hands-on activities and engagement. For components (2) and (3) we will invite a few knowledgeable guest instructors; students will be expected to do some readings and engage in thoughtful discussion.

 

Meet the Instructor(s)

Jennifer Widom

"I'm currently Dean of the School of Engineering, but I'm also a computer science professor whose research and teaching has always revolved around tools and techniques for managing and analyzing data. When I began my career in the 1990s, 'databases' was considered a dull topic whose impact was largely in business. (For the record: I never found it dull.) How things have changed! Now we 'data scientists' are top of the heap.

"I've taught courses about data ranging from a previous Introductory Seminar CS46N Big Data, Big Discoveries, Big Fallacies, to CS102 Working with Data that brought data science to hundreds of students across the university, to CS145 Introduction to Databases that served thousands of computer science majors.

"Before earning my computer science PhD from Cornell I was a serious classical trumpet player, receiving my bachelor's degree from the Indiana University Jacobs School of Music. I'm the spouse of a professor, parent of two grown children, and an avid adventure-traveler, hiker, and scuba diver. During my 2016-17 sabbatical year I traveled the world delivering week-long data science short courses in 20 developing countries on four continents."