Big Data and Critical Thinking
Course Number 1365
Visiting Lecturer Alistair Croll
Fall; Q2; 1.5 credits
Y schedule starting October 14, 1:15pm to 3:15pm
The last few years has seen an explosion of data. Data is being collected at a staggering rate from a wide range of sources as the scale of digital activities has increased. Companies have enormous data on customers-what they buy, how they buy, and where they buy, the professional and social groups to which people belong, employee engagement, and operational performance. Data is sometimes described as the "new gold." But value is not created by data; it is created by the application of data to achieve a business need. Data science seeks to make sense of and gain insights from data.
To manage effectively in this new world requires a fluency in big data and machine learning as well as the skills to think critically about those processes, their application, and appropriately interpret the insights they may (or may not) yield. This course will help students develop the basic data skills, language, and attributes needed to lead an organization towards becoming data-centric and to potentially create data products.
You will learn the basic concepts about data and data science by building the main models in Excel-no programming knowledge is required nor is it needed. After introducing a technique our focus will be on critically thinking through the intuition behind the algorithm to thoughtfully discuss the role of data. What question is being asked? What is being measured in order to answer it? Why and how is the model or algorithm useful in answering it? How confident are we in the predictions? Is there over-fitting of data? How can we visualize it? How does machine learning occur? What implications does the analysis have for managerial action or decision making?
The skills developed in this course are relevant to a wide range of careers because of the ubiquity of data. The course will have value to students interested in entrepreneurship, corporate management, marketing, consulting and financial services. Many of the applications we will discuss will be drawn from different industries and contexts.
The different modules of the course will help students to develop the skills to
- Understand big data techniques such as decision trees and supervised and unsupervised learning and to think critically about asking the right questions, measuring and using the right data, the choice of the appropriate model, and the interpretations we can and cannot draw from the analyses
- Think carefully about data needs and ways to obtain data by scraping public websites
- Design dashboards to visualize and communicate information to generate insights and make decisions
- Organize teams for designing data products by identifying technical, domain and communication needs.
By the end of the course, students will learn what it means to manage in a world with massive amounts of data and the competitive advantages that will flow to organizations that know how to use data to make strategic and business decisions.
Grades will be based on Class Participation, Mid-term quiz, and Project.