While telling stories with data has been part of the news practice since its earliest days, it is in the midst of a renaissance. Graphics desks which used to be deemed as “the art department,” a subfield outside the work of newsrooms, are becoming a core part of newsrooms’ operation. Those people (they often have various titles: data journalists, news artists, graphic reporters, developers, etc.) who design news graphics are expected to be full-fledged journalists and work closely with reporters and editors. The purpose of this class is to learn how to think about the visual presentation of data, how and why it works, and how to doit the right way. We will learn how to make graphs like The New York Times, Vox, Pew, and FiveThirtyEight. In the end, you can share–embed your beautiful charts in publications, blog posts, and websites.
ofrecido por
Visualization for Data Journalism
Universidad de Illinois en Urbana-ChampaignAcerca de este Curso
Basic Python
Habilidades que obtendrás
Basic Python
ofrecido por
Universidad de Illinois en Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
Programa - Qué aprenderás en este curso
Course Orientation
In this module, you will become familiar with the course, your classmates, and the learning environment.
Module 1: Visualization in Newsrooms
This module starts with a summary of the history and emerging trends of data visualization in journalism. You will then explore various types of charts and compare their pros and cons. By doing so, you will be able to recognize a wide variety of graphical forms and evaluate their capabilities/shortcomings as well as what situations each chart type is typically used in storytelling. We will also go through the classic reading by Edward Tufte, The Visual Display of Quantitative Information, and learn how to locate and articulate errors and deception in data visualization.
Module 2: Data and Visual Perception
In this module, we will first look at some examples of successful data visualizations in journalism. We will then drill down on numbers, learning the process of transforming data into information. Next, we will explore theories in visual perception and concepts in visualization and familiarize ourselves with the visual channel ranking—a useful guideline in designing news visualizations. You will evaluate pre-attentive attributes and why they are important in visualizations. You will also have hands-on practice to learn how data wrangling helps us make informed decisions.
Module 3: Narrative Storytelling
In this module, we will learn about the frameworks and techniques that can be used to integrate visualizations into a narrative. You will examine the role messaging and interactions play in drawing readers into a story package that contains greater detail. For the hands-on exercise, you will start creating graphs in Python. You will apply design theories and concepts you previously learned to build line charts, bar charts, and scatter plots.
Module 4: Cognitive Load and Color Perception
In this final module, we will explore some related concepts of cognition and memory in visualization. You will examine the importance of using the “right” amount of color in the right place and apply Gestalt principles to de-clutter your data visualization. In the end, we will work on various exercises to create interactive maps with Python.
Reseñas
Principales reseñas sobre VISUALIZATION FOR DATA JOURNALISM
Well organised and with a lot of commitment from the faculty. I would like to see deeper discussions on most of the topic in the future. Thank you
Thanks very much for great content and the instructor did a great job, and her materials were very use helpful and relevant! Great experience!
It helped to learn a lot about Visualization and enabled with the desired skills of presenting data using python and Jupyter notebook.
Comprehensive course to helping us how to use data for journalism as well as will help us in understanding data in newspapers.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
- es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
- Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si compro el Certificado?
Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.
Is financial aid available?
Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el vínculo de Ayuda económica que está debajo del botón 'Inscribirse' a la izquierda. Se te pedirá que completes una solicitud y recibirás una notificación cuando se apruebe. Obtén más información.
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