Classes

Please note: The classes listed here represent recent offerings at the Journalism School. These include M.S., M.S. in Data Journalism and M.A. courses. Choices vary each semester depending on faculty availability and other considerations. Classes described now may change or be dropped to make room for new additions. We cannot promise that students will gain a seat in any specific class.

Algorithms

Machine learning and data science are integral to processing and understanding large data sets. Whether you're clustering schools or crime data, analyzing relationships between people or businesses, or searching for a needle in a haystack of documents, algorithms can help. Students will generate leads, create insights, and evaluate how to best focus their efforts with large data sets. Topics will include building and managing servers, linear regression, clustering, classification, natural language processing, and tools such as scikit-learn and Mechanical Turk.

Data & Databases

Students will become familiar with a variety of data formats and methods for storing, accessing and processing information. Topics covered include comma-separated documents, interaction with web site APIs and JSON, raw-text document dumps, regular expressions, SQL databases, and more. Students will also tackle less accessible data by building web scrapers and converting difficult-to-use PDFs into useable information.

Data Specialization Workshop

This class is designed to provide students the foundational data and computational skills that will allow them to pursue data-driven stories. Through in-class class instruction, drills and discussion with guest speakers innovating in the field of data journalism, students can refine their skills and be inspired to develop ideas for stories that exist on the frontiers of professional journalism. The workshop will also act as a space for students to discuss and further develop their Master’s projects.

Data Visualization

This course will provide students with hands-on skills in the area of data journalism and information visualization. The class will be project-based, with students working in teams to develop data journalism stories and the accompanying information visualizations. In the process, we will cover a range of data retrieval and analysis tools, as well as current approaches to information visualization from a variety of disciplines. 

Reporting I

In this introductory reporting course, each student will be assigned a beat and will be expected to produce news stories on deadline. Students will learn to think like reporters and to practice the core skills of the trade: developing sources, conducting interviews, structuring a story, writing clearly, and getting the facts right. As data journalists, they will also seek out and analyze data, both to deepen their reporting and to identify promising leads. In this way, the tools and techniques learned during the summer will be immediately applicable as data students begin to develop a journalistic mindset and the capacity to find and produce journalistic stories.

Reporting II

Students will continue to will learn how to apply their data and computational skills to real-world journalism. They will hone their ability to construct a narrative from both quantitative and qualitative sources, how to think critically, how to report under deadline and how to document so that others can replicate and critique their work.

Written Word

In this class, students will produce polished reports that mix qualitative and quantitative observations and analyses and that include "backstory" pieces describing the computation they performed and the basis for the inferences they have drawn in the story.