Data Clustering AlgorithmsText MiningData Visualization (DataViz)Data MiningData Visualization SoftwareTableau SoftwareData VirtualizationInformation Retrieval (IR)Document RetrievalMachine LearningRecommender SystemsProbabilistic Models
데이터 마이닝 특화 과정
Analyze Text, Discover Patterns, Visualize Data. Solve real-world data mining challenges.
30,760명이 이미 등록했습니다.
제공자:
데이터 마이닝 특화 과정일리노이대학교 어버너-섐페인캠퍼스귀하가 습득할 기술
이 전문 분야 정보
최근 조회 34,090회
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.
학습자 경력 결과
50%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
33%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
중급 단계
관련 경험이 어느 정도 필요합니다.
완료하는 데 약 8개월 필요
매주 4시간 권장
영어
자막: 영어, 한국어, 중국어 (간체자)
학습자 경력 결과
50%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
33%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
중급 단계
관련 경험이 어느 정도 필요합니다.
완료하는 데 약 8개월 필요
매주 4시간 권장
영어
자막: 영어, 한국어, 중국어 (간체자)
이 전문 분야에는 6개의 강좌가 있습니다.
데이터 시각화
1,004개의 평가
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.
Text Retrieval and Search Engines
697개의 평가
Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.
Text Mining and Analytics
532개의 평가
This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort.
Pattern Discovery in Data Mining
260개의 평가
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 data-driven phrase mining 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.
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
This 특화 과정 is part of the 100% online Master in Computer Science from 일리노이대학교 어버너-섐페인캠퍼스.
If you are admitted to the full program, your courses count towards your degree learning.
자주 묻는 질문
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Can I just enroll in a single course?
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
Can I take the course for free?
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. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
Is this course really 100% online? Do I need to attend any classes in person?
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
How long does it take to complete the Specialization?
Time to completion can vary widely based on your schedule. Most learners are able to complete the Specialization in 4-5 months.
How often is each course in the Specialization offered?
Each course in the Specialization is offered on a regular schedule with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over.
What background knowledge is necessary?
Comfortable with computer programming in multiple programming languages
Basic knowledge of probability and statistics
Do I need to take the courses in a specific order?
It is recommended that the courses in the Specialization be taken in the order outlined. In the Capstone Project, you will have the opportunity to synthesize your learning in all the courses and apply your combined skills in a final project.
Will I earn university credit for completing the Specialization?
MCS courses in Coursera do not carry University of Illinois credit on their own. Each course has an enhanced for-credit component. You can earn academic credit if you combine an MCS Coursera course with the enhanced for-credit component offered on the University of Illinois platform. Some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
What will I be able to do upon completing the Specialization?
At completion of this Specialization in Data Mining, you will (1) know the basic concepts in pattern discovery and clustering in data mining, information retrieval, text analytics, and visualization, (2) understand the major algorithms for mining both structured and unstructured text data, and (3) be able to apply the learned algorithms to solve real-world data mining problems.
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