Course: CSC233: Intro to Data Analytics Documentation

doingg@union.edu

Welcome

The course website for CSC233, part of the Union College CS curriculum. Here you can find our weekly schedule, assignmnets and resources.

Figure 1.1: Course Banner

Announcements

  • No class Tues
    • I’ll be giving a seminar during common hour, feel free to come!
    • Karp 005, 12:50 - 1:45 pm
  • Final project Colab notebooks due Wednesday
  • Presentations start Thursday (last day of class)
    • still attend even if you are not presenting
  • peer review points (up to 2 pts) can be made-up by commenting on an extra project and putting the link in your check-in notebook
    • comments should be thoughtful and helpful

Office Hours

  • Student/Office Hours:
    • Steinmetz 108B
    • Wednesday 2:00 pm - 3:30 pm
    • Thursday 4:00 pm - 5:30 pm
    • subject to change, check course website for most up-tp-date schedule
    • drop-in or schedule a 15 minute slot: https://calendar.app.google/8bus6pfDvyphR9ar5
    • by appointment for another time or over zoom

Course Description

Data analytics, the process of analyzing, revealing, interpreting and visualizing information concealed inside big data is revolutionizing daily life, as used by companies such as Amazon, Google and Facebook, for the diagnosis of medical conditions or the way medical claims are handled, for investment strategies and real estate pricing, and in academia, with the analysis of historical texts, understanding the deliberations of the Supreme Court or the European Commission, or processing large amounts of genomics data.

In this class, students will be introduced to techniques to acquire data from the web, manipulate and pre-process data into manageable forms, perform analyses from a descriptive and predictive standpoint, and learn the basics of visualization of the result, all with a focus on storytelling through data, enhancing data literacy.

In this course you will use the Python programming language to scrape web data, prepare data for analysis, analyze to produce explainable results, and visualize those results. Throughout we will discuss the pitfalls, ethics and challenges of working with data. A 1-page schedule-at-a-glance is included at the end of the syllabus.

This course requires the pre-approval of the department. For more information, please visit: https://union.edu/advising-registration/pre-approval.