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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About this Course
최근 조회 48,551회
귀하가 습득할 기술
Data Visualization SoftwareTableau SoftwareData VirtualizationData Visualization (DataViz)
Course을(를) 수강하는 학습자
- Data Scientists
- Data Analysts
- Instructional Designers
- Marketing Analysts
- Machine Learning Engineers
강의 계획 - 이 강좌에서 배울 내용
주
1완료하는 데 1시간 필요
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, 1 quiz
6개의 읽기 자료
Welcome to Data Visualization!10m
Syllabus10m
About the Discussion Forums10m
Updating Your Profile10m
Social Media10m
Resources10m
1개 연습문제
Orientation Quiz10m
완료하는 데 4시간 필요
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.
15개 동영상 (총 130분), 2 readings, 1 quiz
15개의 동영상
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
2개의 읽기 자료
Week 1 Overview10m
How the Programming Assignments Work10m
1개 연습문제
Week 1 Quiz20m
주
2완료하는 데 4시간 필요
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.
11개 동영상 (총 85분), 3 readings, 1 quiz
11개의 동영상
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
3개의 읽기 자료
Week 2 Overview10m
Programming Assignment 1: Visualize Data Using a Chart10m
Programming Assignment 1 Rubric10m
주
3완료하는 데 4시간 필요
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.
8개 동영상 (총 72분), 3 readings, 1 quiz
8개의 동영상
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
3개의 읽기 자료
Week 3 Overview10m
Programming Assignment 2: Visualize Network Data10m
Programming Assignment 2 Rubric10m
주
4완료하는 데 2시간 필요
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.
9개 동영상 (총 73분), 1 reading, 1 quiz
9개의 동영상
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
1개의 읽기 자료
Week 4 Overview10m
1개 연습문제
Week 4 Quiz16m
4.5
197개의 리뷰33%
이 강좌를 수료한 후 새로운 경력 시작하기
41%
이 강좌를 통해 확실한 경력상 이점 얻기
20%
급여 인상 또는 승진하기
데이터 시각화의 최상위 리뷰
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.
I found the class to be very informative. The assignments on creating charts and graphs for large data sets were practical and helped me understand the concepts taught in the course.
강사
John C. Hart
Professor of Computer ScienceDepartment of Computer Science
석사 학위 취득 시작
이 강좌은(는) 일리노이대학교 어버너-섐페인캠퍼스의 100% 온라인 Master in Computer Science 중 일부입니다.
전체 프로그램을 수료하면 귀하의 강좌가 학위 취득에 반영됩니다.
일리노이대학교 어버너-섐페인캠퍼스 정보
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.
데이터 마이닝 전문 분야 정보
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.
Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization.
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