Classes

Please note: The classes listed here represent recent offerings at the Journalism School. These include M.S. and M.S. in Data Journalism courses, except for those that are specifically designated as 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.

Covering Campaign Finance

Campaign finance journalism involves much more than simply reporting how much each candidate raised. It means digging deep to find the motivations behind the individuals and organizations supporting a particular political party or candidate. It can also mean identifying candidates using campaign cash as a slush fund to enrich family members and live the high life. More broadly, it means looking beyond campaign finance filings and connecting the dots in order to uncover patterns, networks and relationships that provide insight on the influence of money on politics. This course will provide the foundation of knowledge and skills that enables students to write interesting, thoughtful and impactful stories on the money that fuels election campaigns and political life in this country. 

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 I

This course teaches students how to evaluate and analyze data for appropriateness, context and meaning. Students leave the class knowing how to apply basic statistical methods to numerical data sets. They will also learn how to obtain, clean and load various types of commonly encountered data. They will be drilled on devising interesting, thoughtful and answerable questions to ask of data sets. They will also be taught how to translate the results of their data analysis into clear and concise findings. Visualization in this course will be used primarily for data analysis and story formation, not publication.

Data II

This course is designed to give students who have taken and passed (and hopefully enjoyed) an introductory course on Statistics a more advanced treatment of the process of storytelling with data. This includes: Frameworks and tools for finding, accessing, manipulating and publishing data (APIs, various databases, and some techniques for data "cleaning"); simulation-based approaches to statistical inference when data have special designs (surveys, A/B testing); "models" for data and the stories they tell (regression, trees); and advanced tools for visualization (to explore both data, the effects of data processing, and models). Throughout we will emphasize best practices for documenting your code and analysis ("showing your work").

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. 

Data, Computation, Innovation Workshop I

Students will explore cutting-edge computational and data-oriented forms of storytelling. Through class discussion, guest speakers who are innovating in the field of journalism, and experimentation with novel applications and technologies, students will refine skills they have developed to produce works that exist on the frontiers of professional journalism. The workshop will also act as a space for students to discuss and further develop their final Master’s projects.

Data, Computation, Innovation Workshop II

This course builds on the material from the fall semester workshop and will proceed in similar fashion, with a focus on developing the students’ abilities to tell journalistic stories with data, computation, and new technologies. Throughout the course they will be encouraged to hone fundamental skills such as data analysis and visualization, but they will also explore the potential for emerging tools like sensors, drones, and virtual/augmented reality through workshops and guest lectures. This semester will be paced and organized differently from the fall workshop, which was largely focused on developing one substantial project. This semester, students will be expected to produce work at a faster pace, but the work will be no less rigorous and polished. 

Foundations of Computing

The course is an introduction to the ins and outs of programming and data analysis using the Python programming language, with which students will build a foundation for future coding-intensive classes and journalistic work. After this course, students will be able to find and execute solutions to most any coding- or data-related problem they encounter in the newsroom. The course focuses on cleaning and analysis using the Python programming language, the command line, Jupyter Notebooks, and the data package pandas.

International Newsroom: How to Cover Armies and Spies

Armies and intelligence services are among the most powerful and secretive of institutions, in democracies and authoritarian states alike. They are monopolists of the legitimate use of force, arbiters of war and peace and outsized consumers of national budgets. Covering militaries and spies well and revealingly is hard work that requires preparation and commitment. But it is vital journalism with a public purpose. And occasionally it is journalism that changes the world, from Sy Hersh’s My Lai massacre reporting to Abu Ghraib to Edward Snowden.

This course will prepare students to cover militaries and intelligence services, whether in the United States or abroad. We will take a broad approach, understanding security issues to include human rights, migration and the environment. We will review diverse sourcing strategies, durable story genres and professional and ethical conundrums on the beat. The intention is to equip students to take on defense, intelligence and related human rights reporting as a subject area for daily reporting, longform investigation or as a recurring part of a diversified career, with the understanding that the best sourcing in this field can require years to develop.

Each student will complete a significant piece of narrative reporting accessible from the United States.

We will also undertake a class project about the war in Syria, incorporating data journalism methods and investigative reporting on public records, satellite imagery, user-generated content and confidential source development. The project should provide a strong, accessible body of collaborative work for each enrolled student to highlight in a portfolio. The class will satisfy workshop requirements for both investigative and data concentrators in the M.S. program.

Journalistic Computing

This course unpacks the ways in which data, code and algorithms are reshaping systems of power in the world, training students to be better reporters and to hold the people and institutions behind these systems accountable. This critical view is made possible through rigorous training in data and computing, preparing students to use these tools in an expanded reporting practice that finds and tells new kinds of stories. Our main programming language for the class willl be Python. Each week, students will read and analyze examples of data and computing in service of journalism; and each week we will dig deeper into the technical skills behind such stories with small coding assignments that mix story and technology. The course will end with a final project, an "act of journalism," that might be a story, a data visualization or a new data set or algorithm.

The course is not simply introducing a new web framework for pulling data from a PDF, or a even a new programming language. Instead, we aspire to a rich kind of literacy around data and computing. By “literacy” we mean a trio of concepts – a functional literacy that prepares students to be creative with data and computing; a critical literacy that encourages students to think about data and computing as cultural artifacts; and a rhetorical literacy that highlights the persuasive power inherent in any technology and that casts system design as a social, rather than a purely technical, act. The course will add a uniquely journalistic voice, one that responds to the needs and talents of reporters and helps them find and tell stories in new ways.

Our goals in teaching this course are simple: 1) provide journalists with hands-on experience collecting, processing and analyzing data, 2) demystify the tools and methods behind computing, 3) supply sufficient background so that students might become creators of new technologies, transitioning from tool users to tool makers, and, perhaps most importantly, 4) teach students how to use data and computing, as both sources for finding stories, as well as platforms for telling new kinds of stories.

As mentioned above, our main programming language will be Python, however, we assume NO PRIOR CODING OR DATA KNOWLEDGE. All we ask is that you bring the same journalistic curiosity you have learned in the first half of the program to these new ways of storytelling. We'll take care of the rest.

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.

Tactical Technology for Reporting

In the past fifteen years, digital technologies – from the Internet to the Internet of things - have drastically reshaped the operations of industry and the exercising of individual rights. Essential accountability reporting – on everything from politics to privacy, crime to commerce – relies on a critical understanding of the digital technologies that now permeate public and private life, and also requires a familiarity with how to use technology to report on the issues these technologies generate. Through hands-on exercises and guest lectures from leading reporters, students will learn both the technical skills and essential reporting approaches for working with sources and source material related to digital technology across a range of topic areas. 

Students will also complete a series of in-depth reporting assignments that take technology coverage beyond the consumer/gadget sphere: a technology “profile,” an explanatory piece on a current piece of cyber or technology news, and follow-up pieces on larger technology news stories. In addition to their individual assignments, the class as a whole will work on a larger piece of journalism, likely exploring the origins and aftermath of a major data breach, such as the OPM, HomeDepot or Primera incidents. Through work with experts, original sources, documents and victims, this piece will explore not only how major data breaches happen, but also on the subsequent fallout for individual victims and the public at large.

Using Data to Investigate Across Borders

Exponential amounts of information about the world are being produced daily and journalists everywhere need to have a global mindset if they are to write about organized crime, corruption, human trafficking, global trade and threats to the environment.

We live in an increasingly borderless world. Goods, money, people and ideas flow freely across borders thanks to technology and the liberalization of customs and money controls. We all benefit from globalization and the free flow of commerce that it makes possible. But there’s a dark side: A borderless world also makes it easier for crooks and criminals to do their work.

Around the world, journalists are developing techniques to cope with the globalization of crime, corruption and environmental damage. They are adopting strategies that include the smart use of data and collaboration across borders. The volume and velocity with which information and data are being produced and the variety of open sources currently available make it possible to develop reporting strategies that are truly global.

This course will prepare students to find global data, process and analyze it; and to report on it from New York while working with sources and possibly other journalists overseas. Students will learn skills like doing background checks on people and companies, mining the social web, tracking offshore entities and finding assets and cargo. They will be divided into reporting teams and will be able to find, scrape, consolidate, analyze and visualize data in the context of a big global story by the end of the semester.

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.