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, Subtitles: Korean |
| 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
- Материал для самостоятельного изучения: Welcome to Data Visualization!
- Материал для самостоятельного изучения: Syllabus
- Материал для самостоятельного изучения: About the Discussion Forums
- Материал для самостоятельного изучения: Updating Your Profile
- Материал для самостоятельного изучения: Social Media
- Материал для самостоятельного изучения: Resources
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
- Материал для самостоятельного изучения: Week 1 Overview
- Материал для самостоятельного изучения: How the Programming Assignments Work
- Video: 1.1.1. Some Books on Data Visualization
- Video: 1.1.2. Overview of Visualization
- Video: 1.2.1. 2-D Graphics
- Video: SVG-example
- Video: 1.2.2. 2-D Drawing
- Video: 1.2.3. 3-D Graphics
- Video: 1.2.4. Photorealism
- Video: 1.2.5. Non-Photorealism
- Video: 1.3.1. The Human
- Video: 1.3.2. Memory
- Video: 1.3.3. Reasoning
- Video: 1.3.4. The Human Retina
- Video: 1.3.5. Perceiving Two Dimensions
- Video: 1.3.6. Perceiving Perspective
- Вопрос для обсуждения: Week 1 Discussion
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 to make your visualizations more engaging and effective.
11 videos, 3 readings
- Материал для самостоятельного изучения: Week 2 Overview
- Video: 2.1.1. Data
- Video: 2.1.2. Mapping
- Video: 2.1.3. Charts
- Video: 2.2.1. Glyphs (Part 1)
- Video: 2.2.1. Glyphs (Part 2)
- Video: 2.2.2. Parallel Coordinates
- Video: 2.2.3. Stacked Graphs (Part 1)
- Video: 2.2.3. Stacked Graphs (Part 2)
- Video: 2.3.1. Tufte's Design Rules
- Video: 2.3.2. Using Color
- Материал для самостоятельного изучения: Programming Assignment 1: Visualize Data Using a Chart
- Материал для самостоятельного изучения: Programming Assignment 1 Rubric
- Вопрос для обсуждения: Programming Assignment 1 Help Forum
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
- Материал для самостоятельного изучения: Week 3 Overview
- Video: 3.1.1. Graphs and Networks
- Video: 3.1.2. Embedding Planar Graphs
- Video: 3.1.3. Graph Visualization
- Video: 3.1.4. Tree Maps
- Video: 3.2.1. Principal Component Analysis
- Video: 3.2.2. Multidimensional Scaling
- Video: 3.3.1. Packing
- Материал для самостоятельного изучения: Programming Assignment 2: Visualize Network Data
- Материал для самостоятельного изучения: Programming Assignment 2 Rubric
- Вопрос для обсуждения: Programming Assignment 2 Help Forum
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 techniques from user-interface design to create an effective visualization system.
9 videos, 1 reading
- Материал для самостоятельного изучения: Week 4 Overview
- Video: 4.1.1. Visualization Systems
- Video: 4.1.2. The Information Visualization Mantra: Part 1
- Video: 4.1.2. The Information Visualization Mantra: Part 2
- Video: 4.1.2. The Information Visualization Mantra: Part 3
- Video: 4.1.3. Database Visualization Part: 1
- Video: 4.1.3. Database Visualization Part: 2
- Video: 4.1.3. Database Visualization Part: 3
- Video: 4.2.1. Visualization System Design
Graded: Week 4 Quiz
FAQs
How It Works
Задания курса
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Помощь сокурсников
Общайтесь с тысячами других учащихся: обсуждайте идеи, материалы курса и помогайте друг другу осваивать новые понятия.
Сертификаты
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Creators
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
| Purchase Course | |
|---|---|
| Access to course materials | Available |
| Access to graded materials | Available |
| Receive a final grade | Available |
| Earn a shareable Course Certificate | Available |
Ratings and Reviews
Learning curve is too steep in week 3.
This is an excellent course. The lecture topics were relevant and the course was well organized. The programming assignments fit well with the course objectives. I highly recommend this class to anyone creating data visualizations.
give us big picture of visualizations and share lots of practical skills. also cover some mechanisms of why visualization through introducing human visual perception system. However, the tool in this course is mainly the tableu which is a business software that is not free.
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Very interesting course that shows you how to present your data set in a way that you can actually deduce what is going on in one look.I like how Professor John C. Hart had shared with us that we are building Data Visualization Charts eventually for Human Audience, thus, a little bit understanding about the human eyes, ears, brain is good.