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Interactive Data Visualization

Instructor(s):

Dates:

February 13, 2015 to March 13, 2015 June 12, 2015 to July 10, 2015 October 30, 2015 to November 27, 2015 February 12, 2016 to March 11, 2016 June 10, 2016 to July 08, 2016 October 28, 2016 to November 25, 2016 February 10, 2017 to March 10, 2017 June 09, 2017 to July 07, 2017 October 27, 2017 to November 24, 2017 February 09, 2018 to March 09, 2018 June 08, 2018 to July 06, 2018 October 26, 2018 to November 30, 2018

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Interactive Data Visualization

taught by Galit Shmueli or Catherine Plaisant

Aim of Course:

In this online course, “Interactive Data Visualization,” you will learn about the interactive exploration of data, and how it is achieved using state-of-the-art data visualization software. Participants will learn to explore a range of different data types and structures. They will learn about various interactive techniques for manipulating and examining the data and producing effective visualizations.

 

The course is very hands-on in terms of the learning process. Participants will be guided through an exploration of quantitative business data to discern meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities.

This course may be taken individually (one-off) or as part of a certificate program.

Course Program:

WEEK 1

  • Information visualization characterization and history
  • Elements of visual perception
  • Software introduction and data preparation (merging data, getting started, export)
WEEK 2
  • Interaction techniques
  • Distribution analysis
  • Hands-on visual exploration of business data
WEEK 3
  • Time Series
  • Multivariate views (scatterplots, parallel coordinate plots, trellising)
  • Treemaps for hierarchical data
WEEK 4
  • Specialized visualizations
  • Video demonstrations of novel techniques
  • From visualization to visual analytics


HOMEWORK:

Homework in this course consists of guided exercises using state of the art software.

In addition to assigned readings, this course also has an end of course data modeling project, and example software files.


Interactive Data Visualization

Instructor(s):

Dates:
February 13, 2015 to March 13, 2015 June 12, 2015 to July 10, 2015 October 30, 2015 to November 27, 2015 February 12, 2016 to March 11, 2016 June 10, 2016 to July 08, 2016 October 28, 2016 to November 25, 2016 February 10, 2017 to March 10, 2017 June 09, 2017 to July 07, 2017 October 27, 2017 to November 24, 2017 February 09, 2018 to March 09, 2018 June 08, 2018 to July 06, 2018 October 26, 2018 to November 30, 2018

Course Fee: $589

Do you meet course prerequisites? What about book & software? (Click here to learn more)

Tuition Savings:  When you register online for 3 or more courses, $200 is automatically deducted from the total tuition. (This offer cannot be combined and is only applicable to courses of 3 weeks or longer.)

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Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.

Interactive Data Visualization

taught by Galit Shmueli or Catherine Plaisant

Who Should Take This Course:

Statistical analysts and data miners who need to explore and graph multivariate data, either to form impressions of the data or as a preliminary step to performing statistical tests or building models.

Level:

beginning-intermediate

Prerequisite:
These are listed for your benefit so you can determine for yourself, whether you have the needed background, whether from taking the listed courses, or by other experience.

If you are unclear as to whether you have mastered the above requirements, try these placement tests.

Organization of the Course:

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement: about 15 hours per week, at times of  your choosing.


Credit:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course, 5.0 CEU's and a record of course completion will be issued by The Institute, upon request.

Course Text:
The required text for this course is Now You See It: Simple Visualization Techniques for Quantitative Analysis by Stephen Few. Please make sure you have the book prior to the beginning of the course.

Software:

The use of Tableau software is illustrated and access to this program will be provided in the first lesson.

Some students also use Spotfire, but it is not available as part of the course.  Using R?  Please see the courses "R Graphics" and "R ggplot2" (see "Related Courses").


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