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.
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Data Mining SpecializationUniversity of Illinois at Urbana-ChampaignAbout this Course
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Learner Career Outcomes
30%
started a new career after completing these courses
35%
got a tangible career benefit from this course
15%
got a pay increase or promotion
Shareable Certificate
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Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 15 hours to complete
English
Subtitles: English, Korean, Chinese (Simplified)
Skills you will gain
Data Visualization SoftwareTableau SoftwareData VirtualizationData Visualization (DataViz)
Learner Career Outcomes
30%
started a new career after completing these courses
35%
got a tangible career benefit from this course
15%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 1 of 6 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 15 hours to complete
English
Subtitles: English, Korean, Chinese (Simplified)
Offered by
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.
Start working towards your Master's degree
This course is part of the 100% online Master in Computer Science from University of Illinois at Urbana-Champaign.
If you are admitted to the full program, your courses count towards your degree learning.
Syllabus - What you will learn from this course
2 hours to complete
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.
2 hours to complete
6 readings
6 readings
Welcome to Data Visualization!10m
Syllabus10m
About the Discussion Forums10m
Updating Your Profile10m
Social Media10m
Resources10m
1 practice exercise
Orientation Quiz30m
4 hours to complete
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.
4 hours to complete
15 videos (Total 130 min), 2 readings, 1 quiz
15 videos
1.1.1. Some Books on Data Visualization3m
1.1.2. Overview of Visualization11m
1.2.1. 2-D Graphics10m
SVG-example1m
1.2.2. 2-D Drawing9m
1.2.3. 3-D Graphics9m
1.2.4. Photorealism9m
1.2.5. Non-Photorealism5m
1.3.1. The Human10m
1.3.2. Memory12m
1.3.3. Reasoning7m
1.3.4. The Human Retina9m
1.3.5. Perceiving Two Dimensions8m
1.3.6. Perceiving Perspective8m
2 readings
Week 1 Overview10m
How the Programming Assignments Work10m
1 practice exercise
Week 1 Quiz30m
4 hours to complete
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.
4 hours to complete
11 videos (Total 85 min), 3 readings, 1 quiz
11 videos
2.1.1. Data7m
2.1.2. Mapping9m
2.1.3. Charts9m
2.2.1. Glyphs (Part 1)4m
2.2.1. Glyphs (Part 2)6m
2.2.2. Parallel Coordinates8m
2.2.3. Stacked Graphs (Part 1)5m
2.2.3. Stacked Graphs (Part 2)6m
2.3.1. Tufte's Design Rules12m
2.3.2. Using Color11m
3 readings
Week 2 Overview10m
Programming Assignment 1: Visualize Data Using a Chart10m
Programming Assignment 1 Rubric10m
4 hours to complete
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.
4 hours to complete
8 videos (Total 72 min), 3 readings, 1 quiz
8 videos
3.1.1. Graphs and Networks8m
3.1.2. Embedding Planar Graphs11m
3.1.3. Graph Visualization13m
3.1.4. Tree Maps9m
3.2.1. Principal Component Analysis8m
3.2.2. Multidimensional Scaling6m
3.3.1. Packing12m
3 readings
Week 3 Overview10m
Programming Assignment 2: Visualize Network Data10m
Programming Assignment 2 Rubric10m
2 hours to complete
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.
2 hours to complete
9 videos (Total 73 min), 1 reading, 1 quiz
9 videos
4.1.1. Visualization Systems3m
4.1.2. The Information Visualization Mantra: Part 19m
4.1.2. The Information Visualization Mantra: Part 29m
4.1.2. The Information Visualization Mantra: Part 35m
4.1.3. Database Visualization Part: 112m
4.1.3. Database Visualization Part: 28m
4.1.3. Database Visualization Part: 39m
4.2.1. Visualization System Design14m
1 reading
Week 4 Overview10m
1 practice exercise
Week 4 Quiz30m
Reviews
TOP REVIEWS FROM DATA VISUALIZATION
by GDJun 1, 2017
A fairly interesting course with a good instructor. The course gave me a chance to play with my visualization tools in order to expand my usage rather than being in a rush to complete my tasks.
by GCNov 16, 2020
Very useful course. It enlightens my ways to data visualization. I knew some concepts, but in a disorganized way and not knowing how. This course fills these gaps. It is tremendously helpful.
by MKApr 5, 2018
Good course, very well structured and with interesting assignments. Some (especially first) lessons are more of a general culture but most are very helpful and allow to learn a lot of things.
by VCApr 26, 2020
I enjoyed a great deal of this course. However, I felt that the course could be improved by adding in a few programming implementations of visualization. Thank you for teaching this subject!
About the Data Mining Specialization
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp.
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