About this course: Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.
Created by: University of Illinois at Urbana-Champaign
Taught by: John C. Hart, Professor of Computer Science
Department of Computer Science
| Basic Info |
Course 1 of 6 in the
Data Mining Specialization.
|
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Course Orientation
You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
6 readings
Graded: Orientation Quiz
Week 1: The Computer and the Human
In this week's module, you will learn what data visualization is, how it's used, and how computers display information. You'll also explore different types of visualization and how humans perceive information.
15 videos, 2 readings
Graded: Week 1 Quiz
WEEK 2
Week 2: Visualization of Numerical Data
In this week's module, you will start to think about how to visualize data effectively. This will include assigning data to appropriate chart elements, using glyphs, parallel coordinates, and streamgraphs, as well as implementing principles of design and color...
11 videos, 3 readings
Graded: Programming Assignment 1
WEEK 3
Week 3: Visualization of Non-Numerical Data
In this week's module, you will learn how to visualize graphs that depict relationships between data items. You'll also plot data using coordinates that are not specifically provided by the data set.
8 videos, 3 readings
Graded: Programming Assignment 2
WEEK 4
Week 4: The Visualization Dashboard
In this week's module, you will start to put together everything you've learned by designing your own visualization system for large datasets and dashboards. You'll create and interpret the visualization you created from your data set, and you'll also apply te...
9 videos, 1 reading
Graded: Week 4 Quiz
FAQs
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University of Illinois at 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.
Pricing
| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
Ratings and Reviews
It should have more assignment and handson, It should also teach how to use any visualization tool for doing assignment.
A really helpful primer. I lays out a broad map of the concepts that inform the craft of data visualization and provides a basic set of examples and exercises. It's up to the student to take this map and really explore each if s/he hopes to master the subject. Thank you, Professor Hart!
i really enjoyed this course and get gain more knowledge
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The course introduces one to more parameters and considerations to account for when building data visualizations than they would probably imagine. From human perception of visuals to 2-D and 3-D rendering to ideal plots for different series of data, the course covers a lot of ground and introduces some very interesting concepts. The programming assignments don't really require programming knowledge if you are able to generate graphs using off the shelf tools. One thing to keep in mind is that although the course suggests you can build a web site or page with your visualizations if desired, the assignment submissions do not allow for the submission of a URL link to a website or a page. Links can however be embedded into additional comments associated with the submission.