Este curso forma parte de Programa especializado: Vital Skills for Data Science

4.8

estrellas

15 calificaciones

Danielle Szafir

3017 ya inscrito

Ofrecido Por

Parte del título de grado Master of Science in Data Science
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Programa especializado: Vital Skills for Data ScienceUniversidad de Colorado en Boulder

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Data is everywhere. Charts, graphs, and other types of information visualizations help people to make sense of this data. This course explores the design, development, and evaluation of such information visualizations. By combining aspects of design, computer graphics, HCI, and data science, you will gain hands-on experience with creating visualizations, using exploratory tools, and architecting data narratives. Topics include user-centered design, web-based visualization, data cognition and perception, and design evaluation.
This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

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Curso 4 de 4 en

Programa especializado: Vital Skills for Data Science

Nivel intermedio

Python, foundation in Data Science

Aprox. 14 horas para completar

Inglés (English)

Qué aprenderás

Develop a toolkit for exploring and communicating complex data using visualization
Produce basic data visualizations using a chosen dataset
Compare methods for visualizing data and understand how these methods may guide users towards different conclusions
Evaluate how effectively a visualization conveys target data

Habilidades que obtendrás

Evaluation Design
Visualizing data with Altair
User-Centered Design (Create basic visualizations that match data and user needs)
Task Analysis (Define elements of a data analysis and/or communication problem)

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 4 de 4 en

Programa especializado: Vital Skills for Data Science

Nivel intermedio

Python, foundation in Data Science

Aprox. 14 horas para completar

Inglés (English)

Instructor

Calificación del instructor

4,59/5 (5 calificaciones)

Danielle Szafir

Assistant Professor

ATLAS Institute and Computer Science

3017 alumnos

1 curso

Ofrecido por

Universidad de Colorado en Boulder

Comienza a trabajar para obtener tu maestría

Este curso es parte de Master of Science in Data Science completamente en línea de Universidad de Colorado en Boulder. Si te aceptan en el programa completo, tus cursos cuentan para tu título de grado.

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Programa - Qué aprenderás en este curso

Semana1

Semana 1

8 horas para completar

Basics of Design

In this module, you will learn the foundations of visualization design. You will walk through the key components of a visualization, how we effectively represent data using channels like color, size, and position, and some ground rules for honest and effective visualization. You will also gain preliminary exposure to Altair, a Python library for rapidly generating interactive visualizations. Each week will also include either two readings or one reading and one notebook activity.

8 horas para completar

13 videos (Total 156 minutos), 13 lecturas, 1 cuestionario

13 videos

Course Overview3mWhy Visualization?13mA Grammar of Graphics10mIntroduction to Altair6mHands on with Altair - Part 113mHands on with Altair - Part 211mMapping Basics10mMapping Tips11mColor17mRules of Thumb16mIntroduction to Interaction12mInteractions Part 113mInteractions Part 212m

13 lecturas

Welcome and Where to Find Help 10mInformation on Peer Reviews10mA Tour Through the Visualization Zoo10mData Humanism: The Revolutionary Future of Data Visualization10mVega-Lite: A Grammar of Interactive Graphics10mWorkshop Overview of Altair Basics10mExploratory Data Visualization with Altair10mThe Structure of the Information Visualization Design Space10mExtra Resources: Data Types, Graphical Marks, and Visual Encoding Channels10mThe Good, the Bad, and the Biased10mExtra Resources: WTF Visualizations10mExtra Resources: Ethical Dimensions of Visualization Research10mToward a Deeper Understanding of the Role of Interaction in Information Visualization10m

1 ejercicio de práctica

Week 1 Quiz30m

Semana2

Semana 2

4 horas para completar

User Needs

In this module, you will learn how to choose the right visualization for a given scenario. You will learn how to reason about the different kinds of questions people ask with visualization and, how to align your design with that task. The module will cover basics of task analysis, methods for task elicitation, and foundational knowledge of visual perception for design. Each week will also include two external readings or one reading and one notebook activity.

4 horas para completar

9 videos (Total 110 minutos), 7 lecturas, 1 cuestionario

9 videos

Visualization Tasks12mTask Elicitation15mBasic Design Methods11mDesign Studies17mPerception Overview5mPreattention13mAttention & Search14mUncertainty10mEthical Questions8m

7 lecturas

A Design Space of Visualization Tasks10mDesign Study Methodology: Reflections from the Trenches and the Stacks10mOverview: The Design, Adoption, and Analysis of a Visual Document Mining Tool for Investigative Journalists10mCriteria for Rigor in Visualization Design Study10mOn the Prospects for a Science of Visualization10mAttention and Visual Memory in Visualization and Computer Graphics10mWhy Authors Don't Visualize Uncertainty10m

1 ejercicio de práctica

Week 2 Quiz30m

Semana3

Semana 3

3 horas para completar

Evaluation

In this module, you will learn how to assess the effectiveness of your visualization. You will learn both qualitative and quantitative approaches for evaluating visualizations as well as how to isolate key elements for assessment and iteration. The module will cover basics of insight-based evaluation, interview studies, and experimental design and analysis. Each week will also include two external readings or one reading and one notebook activity.

3 horas para completar

7 videos (Total 80 minutos), 7 lecturas, 1 cuestionario

7 videos

Module Overview1mEvaluation Overview8mDefining Insight12mQualitative Evaluation15mExperimental Evaluation Part 113mExperimental Evaluation Part 217mEvaluation Trade-Offs11m

7 lecturas

Empirical Studies in Information Visualization: Seven Scenarios10mToward Measuring Visualization Insight10mCriteria for Rigor in Visualization Design Study10mExperimental Research in HCI10mA Design Space of Vision Science Methods for Visualization Research10mEmpirical Studies in Information Visualization: Seven Scenarios10mEvaluating Information Visualizations10m

1 ejercicio de práctica

Week 3 Quiz30m

Acerca de Programa especializado: Vital Skills for Data Science

Vital Skills for Data Science introduces students to several areas that every data scientist should be familiar with. Each of the topics is a field in itself. This specialization provides a "taste" of each of these areas which will allow the student to determine if any of these areas is something they want to explore further. In this specialization, students will learn about different applications of data science and how to apply the steps in a data science process to real life data. They will be introduced to the ethical questions every data scientist should be aware of when doing an analysis. The field of cybersecurity makes the data scientist aware of how to protect their data from loss.

This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder. Logo image by JJ Ying on Unsplash

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 me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. 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 auditar el curso sin costo.
¿Cuál es la política de reembolsos?
Si estás suscrito, obtienes una prueba gratis de 7 días, que podrás cancelar cuando desees sin ningún tipo de penalidad. Una vez transcurrido ese tiempo, no realizamos reembolsos. No obstante, puedes cancelar tu suscripción cuando quieras. Consulta nuestra política completa de reembolsos.
¿Hay ayuda económica disponible?
Sí. En ciertos programas de aprendizaje, puedes postularte para recibir ayuda económica o una beca en caso de no poder costear los gastos de la tarifa de inscripción. Si hay ayuda económica o becas disponibles para tu selección de programa de aprendizaje, verás un enlace para postularte en la página de descripción.

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Fundamentals of Data Visualization

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Qué aprenderás

Habilidades que obtendrás