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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이 강좌에 대하여
학습자 경력 결과
30%
33%
14%
귀하가 습득할 기술
학습자 경력 결과
30%
33%
14%
제공자:

일리노이대학교 어버너-섐페인캠퍼스
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.
석사 학위 취득 시작
강의 계획 - 이 강좌에서 배울 내용
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.
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.
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.
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.
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.
검토
데이터 시각화의 최상위 리뷰
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.
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.
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.
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!
데이터 마이닝 특화 과정 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.

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