Principios esenciales de diseño en Tableau (Coursera)

Offered by Universidad Austral,
Principios esenciales de diseño en Tableau (Coursera)

En este curso, analizarás y aplicarás principios de diseño esenciales para tus visualizaciones en Tableau. Este curso asume que comprendes las herramientas dentro de Tableau y tienes algún conocimiento de los conceptos fundamentales de visualización de datos. Definirás y examinarás las similitudes y diferencias del análisis exploratorio y estudio, así como comenzarás a hacerte las preguntas correctas sobre lo que se necesita en una visualización.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Evaluarás cómo trabajan juntos los datos y el diseño, incluida la forma de elegir la representación visual adecuada para tus datos y la diferencia entre imágenes efectivas e ineficaces. Aplicarás principios efectivos de diseño de mejores prácticas a tus visualizaciones de datos y podrá ilustrar ejemplos de uso estratégico del contraste para resaltar elementos importantes. Evaluarás los atributos preatentivos y por qué son importantes en las visualizaciones. Examinarás la importancia de usar la cantidad "correcta" de color y en el lugar correcto y podrás aplicar los principios de diseño para ordenar tu visualización de datos.

What You Will Learn

  • Examinar y mejorar una visualización ineficaz.
  • Aplicar las mejores prácticas de visualización
  • Crear y diseñar visualizaciones que funcionen mejor para el público objetivo

Syllabus

WEEK 1
Descubriendo imágenes eficaces e ineficaces
En este primer módulo, vamos a comenzar con información básica sobre cómo el cerebro humano percibe el mundo y luego descubrirás imágenes eficaces e ineficaces. Al final de este módulo, podrás reconocer cómo se relaciona el cerebro con el diseño visual. Conocerás la diferencia entre el diseño cognitivo versus el diseño perceptivo. Aprenderás las diversas opciones de visualización que ofrece Tableau y algunas de sus ventajas y desventajas. Discutirás por qué las buenas prácticas éticas juegan en el diseño de visualizaciones. También comenzarás a examinar visualizaciones ineficaces y aprenderá a mejorarlas.

WEEK 2
Percepción visual y carga cognitiva
En este módulo explorarás conceptos específicos de la visualización de datos que aplican los conceptos aprendidos en el módulo anterior sobre cómo funciona el cerebro humano. Podrás definir la carga cognitiva y lo que significa el desorden desde una perspectiva de la visualización. Podrás ilustrar visualmente los principios de la percepción visual y utilizar el contraste para mejorar tus visualizaciones. Podrás definir y utilizar atributos preatentivos como el color para realizar visualizaciones efectivas.

WEEK 3
Diseño de las mejores prácticas
En este módulo, revisarás algunos de los conceptos introducidos en el módulo anterior. Podrás aplicar los principios de Gestalt y aprovechar los atributos de atención previa en tus visualizaciones. Examinarás el papel de la accesibilidad y la estética en tus creaciones.

WEEK 4
Diseñar para comprender
Después de completar este módulo, podrás diseñar tus visualizaciones para un público objetivo y con un propósito. Podrás identificar la conexión entre datos, relaciones y un buen diseño visual. Implementarás herramientas de diseño y obtendrás consejos adicionales en tus visualizaciones.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Visualización de Datos con Python (Coursera) Coursera
IBM

Visualización de Datos con Python (Coursera)

"Una imagen vale mas que mil palabras". Todos estamos familiarizados con esta expresión. Se aplica especialmente cuando se trata de explicar la información obtenida del análisis de conjuntos de datos cada vez más grandes. La visualización de datos juega un papel esencial en la representación de datos tanto a pequeña como a gran escala. Una de las habilidades clave de un científico de datos es la capacidad de contar una historia convincente, visualizando datos y hallazgos de una manera accesible y estimulante

Nov 23rd 2026
3 Weeks
Julia Scientific Programming (Coursera) Coursera
University of Cape Town

Julia Scientific Programming (Coursera)

This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more.

Nov 9th 2026
4 Weeks
Data Science with R - Capstone Project (Coursera) Coursera
IBM

Data Science with R - Capstone Project (Coursera)

In this capstone course, you will apply various data science skills and techniques that you have learned as part of the previous courses in the IBM Data Science with R Specialization or IBM Data Analytics with Excel and R Professional Certificate. For this project, you will assume the role of a Data Scientist who has recently joined an organization and be presented with a challenge that requires data collection, analysis, basic hypothesis testing, visualization, and modeling to be performed on real-world datasets.

Nov 9th 2026
5-12 Weeks
Fundamentals of Machine Learning in Finance (Coursera) Coursera
New York University Tandon School of Engineering

Fundamentals of Machine Learning in Finance (Coursera)

The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its performance.

Nov 9th 2026
4 Weeks
Data Visualization for Genome Biology (Coursera) Coursera
University of Toronto

Data Visualization for Genome Biology (Coursera)

The past decade has seen a vast increase in the amount of data available to biologists, driven by the dramatic decrease in cost and concomitant rise in throughput of various next-generation sequencing technologies, such that a project unimaginable 10 years ago was recently proposed, the Earth BioGenomes Project, which aims to sequence the genomes of all eukaryotic species on the planet within the next 10 years. So while data are no longer limiting, accessing and interpreting those data has become a bottleneck. One important aspect of interpreting data is data visualization. This course introduces theoretical topics in data visualization through mini-lectures, and applied aspects in the form of hands-on labs.

Nov 16th 2026
5-12 Weeks
Excel Power Tools for Data Analysis (Coursera) Coursera
Macquarie University

Excel Power Tools for Data Analysis (Coursera)

Welcome to Excel Power Tools for Data Analysis. In this four-week course, we introduce Power Query, Power Pivot and Power BI, three power tools for transforming, analysing and presenting data. Excel's ease and flexibility have long made it a tool of choice for doing data analysis, but it does have some inherent limitations: for one, truly "big" data simply does not fit in a spreadsheet and for another, the process of importing and cleaning data can be a repetitive, time-consuming and error-prone.

Nov 9th 2026
4 Weeks
Accounting Data Analytics with Python (Coursera) Coursera
University of Illinois at Urbana-Champaign

Accounting Data Analytics with Python (Coursera)

This course focuses on developing Python skills for assembling business data. It will cover some of the same material from Introduction to Accounting Data Analytics and Visualization, but in a more general purpose programming environment (Jupyter Notebook for Python), rather than in Excel and the Visual Basic Editor. These concepts are taught within the context of one or more accounting data domains (e.g., financial statement data from EDGAR, stock data, loan data, point-of-sale data).

Nov 9th 2026
5-12 Weeks
Essential Epidemiologic Tools for Public Health Practice (Coursera) Coursera
Johns Hopkins University

Essential Epidemiologic Tools for Public Health Practice (Coursera)

In order to make a difference in the health and well-being of a population, we must understand the burden of all problems and conditions that affect the population, as well as how well our efforts to mitigate these problems are actually working. This course provides you with some essential skills and tools that will enhance your ability to describe and understand the health of your community

Nov 9th 2026
4 Weeks
Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Nov 16th 2026
5-12 Weeks
Code Free Data Science (Coursera) Coursera
University of California, San Diego

Code Free Data Science (Coursera)

The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data.

Nov 23rd 2026
4 Weeks
Big Data Analysis Deep Dive (Coursera) Coursera
Alibaba Cloud Academy

Big Data Analysis Deep Dive (Coursera)

The job market for architects, engineers, and analytics professionals with Big Data expertise continues to increase. The Academy’s Big Data Career path focuses on the fundamental tools and techniques needed to pursue a career in Big Data. This course includes: data processing with python, writing and reading SQL queries, transmitting data with MaxCompute, analyzing data with Quick BI, using Hive, Hadoop, and spark on E-MapReduce, and how to visualize data with data dashboards. Work through our course material, learn different aspects of the Big Data field, and get certified as a Big Data Professional!

Nov 23rd 2026
5-12 Weeks