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New York University (NYU)

Information Visualization: Foundations

New York University (NYU) via Coursera

Overview

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The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on information visualization and to design and develop advanced applications for visual data analysis.

This course aims at introducing fundamental knowledge for information visualization. The main goal is to provide the students with the necessary “vocabulary” to describe visualizations in a way that helps them reason about what designs are appropriate for a given problem. This module also gives a broad overview of the field of visualization, introducing its goals, methods and applications.

A learner with some or no previous knowledge in Information Visualization will get a sense of what visualization is, what it is for and in how many different situations it can be applied; will practice to describe data in a way that is useful for visualization design; will familiarize with fundamental charts to talk about the concept of visual encoding and decoding.

Syllabus

  • Introduction to Information Visualization
  • Data Abstraction
  • Fundamental Graphs and Data Transformation
  • Graphical Components and Mapping Strategies

Taught by

Enrico Bertini and Cristian Felix

Reviews

5.0 rating, based on 1 Class Central review

4.5 rating at Coursera based on 208 ratings

Start your review of Information Visualization: Foundations

  • Excellent course from a respected industry leader! Very well structured. Covers both theoretical aspects and their practical applications.
    Nicely worked out videos (the instructor took the guidelines from Barbara Oakley / Learning How To Learn on how to make a good MOOC seriously).
    The exercises took me significantly more time than announced, at least 3 hours for each of the 2 exercises, but it was well worth it. It has been a while since I enjoyed Coursera's peer review that much, they added value to my learning experience, good feedback on my work plus examples on how other students approached the problems.
    This is a candidate course for class central's Top50.

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