This course is part of the Data Mining Specialization

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1,323 ratings

John C. Hart

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Part of the Master of Computer Science degree
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Data Mining SpecializationUniversity of Illinois at Urbana-Champaign

About this Course

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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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 6 in the

Data Mining Specialization

Approx. 16 hours to complete

English

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Skills you will gain

Data Visualization Software
Tableau Software
Data Virtualization
Data Visualization (DataViz)

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 6 in the

Data Mining Specialization

Approx. 16 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.75/5 (104 Ratings)

John C. Hart

Professor of Computer Science

Department of Computer Science

127,240 Learners

9 Courses

Offered by

University of Illinois at Urbana-Champaign

Start working towards your Master's degree

This course is part of the 100% online Master of Computer Science from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your courses count towards your degree learning.

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Syllabus - What you will learn from this course

Content Rating96%(7,789 ratings)

Week

Week 1

2 hours to complete

Course Orientation

2 hours to complete

6 readings

4 hours to complete

Week 1: The Computer and the Human

4 hours to complete

15 videos (Total 130 min), 2 readings, 1 quiz

15 videos

Week 1 Introduction11m

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

Week

Week 2

4 hours to complete

Week 2: Visualization of Numerical Data

4 hours to complete

11 videos (Total 85 min), 3 readings, 1 quiz

Week

Week 3

4 hours to complete

Week 3: Visualization of Non-Numerical Data

4 hours to complete

8 videos (Total 72 min), 3 readings, 1 quiz

Week

Week 4

2 hours to complete

Week 4: The Visualization Dashboard

2 hours to complete

9 videos (Total 73 min), 1 reading, 1 quiz

9 videos

Week 4 Introduction55s

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

4.5

301 reviews

5 stars
64.62%
4 stars
24.79%
3 stars
6.19%
2 stars
2.49%
1 star
1.88%

TOP REVIEWS FROM DATA VISUALIZATION

by ANApr 23, 2022

Excellent introduction to data visualization. The lectures are interesting and high quality. I used D3.js to try different approaches, which was a bit time consuming but interesting.

by ASNov 6, 2016

This is a great course. I highly recommend this course if you are looking to better visualize your data for an audience, and how people perceive graphs.

by ADJun 3, 2017

It provides me with the base to transmit to the user the data analysis made in a visual way easy for them to understand and take decision.

by ZOAug 11, 2019

Thank you for this amazing course, for.me the most enjoyable and amazing tool for this course is how encouraging me to find real life data repository and learn how to visualize it.

View all reviews

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.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Data Visualization

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