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    • Data Mining

    필터링 기준

    "data mining"에 대한 173개의 결과

    • University of Illinois at Urbana-Champaign

      University of Illinois at Urbana-Champaign

      Data Mining

      획득할 기술: Accounting, Algorithms, Analysis, Applied Machine Learning, Bayesian Statistics, Big Data, Bioinformatics, Business Analysis, Calculus, Computational Logic, Computer Architecture, Computer Graphics, Computer Programming, Data Analysis, Data Clustering Algorithms, Data Management, Data Mining, Data Structures, Data Visualization, Databases, Distributed Computing Architecture, Financial Analysis, General Statistics, Geovisualization, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Natural Language Processing, Probability & Statistics, SQL, Statistical Analysis, Statistical Programming, Theoretical Computer Science, Visualization (Computer Graphics)

      4.5

      (2.7k개의 검토)

      Intermediate · Specialization

    • University of Colorado Boulder

      University of Colorado Boulder

      Data Mining Foundations and Practice

      획득할 기술: Algorithms, Data Clustering Algorithms, Data Management, Data Warehousing, Theoretical Computer Science

      3.0

      (7개의 검토)

      Intermediate · Specialization

    • University of Michigan

      University of Michigan

      Applied Data Science with Python

      획득할 기술: Algorithms, Analysis, Applied Machine Learning, Artificial Neural Networks, Computational Logic, Computer Programming, Data Analysis, Data Management, Data Mining, Data Visualization, Econometrics, Extract, Transform, Load, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Mathematical Theory & Analysis, Mathematics, Matplotlib, Natural Language Processing, Network Analysis, Probability & Statistics, Programming Principles, Python Programming, Regression, Social Network, Statistical Machine Learning, Statistical Programming, Theoretical Computer Science

      4.5

      (31.9k개의 검토)

      Intermediate · Specialization

    • Coursera Project Network

      Coursera Project Network

      Introduction to Data Analysis using Microsoft Excel

      획득할 기술: Lookup Table, Pivot Table, Business Analysis, Microsoft Excel, Data Analysis Software, Spreadsheet Software, Linear Algebra, Data Mining, Mathematical Theory & Analysis, Analysis, Mathematics, Data Analysis

      4.7

      (169개의 검토)

      Intermediate · Guided Project

    • Google

      Google

      Google Data Analytics

      획득할 기술: Algorithms, Analysis, Application Development, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Structures, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Econometrics, Entrepreneurship, Experiment, Extract, Transform, Load, Feature Engineering, Finance, General Statistics, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Plot (Graphics), Presentation, Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software, Software Engineering, Software Security, Spreadsheet, Spreadsheet Software, Statistical Analysis, Statistical Programming, Statistical Visualization, Storytelling, Strategy and Operations, Theoretical Computer Science

      4.8

      (62.3k개의 검토)

      Beginner · Professional Certificate

    • University of Colorado Boulder

      University of Colorado Boulder

      Data Mining Methods

      획득할 기술: Algorithms, Data Clustering Algorithms, Theoretical Computer Science

      Intermediate · Course

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      University of Illinois at Urbana-Champaign

      University of Illinois at Urbana-Champaign

      Predictive Analytics and Data Mining

      획득할 기술: Statistical Programming, Financial Analysis, Bayesian Statistics, R Programming, Machine Learning Algorithms, Machine Learning, Algebra, Data Management, Analytics, Data Mining, Analysis, Research and Design, Big Data, Econometrics, Entrepreneurship, Algorithms, Market Research, Supply Chain and Logistics, Mathematics, Probability & Statistics, Theoretical Computer Science, Data Analysis

      4.4

      (125개의 검토)

      Intermediate · Course

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      University of Illinois at Urbana-Champaign

      University of Illinois at Urbana-Champaign

      Pattern Discovery in Data Mining

      획득할 기술: Market (Economics), Algorithms, Data Mining, Machine Learning, Applied Machine Learning, Theoretical Computer Science, Analysis, Computer Programming, Probability & Statistics, Data Analysis

      4.3

      (303개의 검토)

      Mixed · Course

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      University of Illinois at Urbana-Champaign

      University of Illinois at Urbana-Champaign

      Cluster Analysis in Data Mining

      획득할 기술: Machine Learning Algorithms, Machine Learning, Natural Language Processing, Data Clustering Algorithms, Algorithms, Analysis, Data Mining, Calculus, Theoretical Computer Science, Probability & Statistics, Data Analysis, Mathematics

      4.5

      (393개의 검토)

      Mixed · Course

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      University of Colorado Boulder

      University of Colorado Boulder

      Data Mining Pipeline

      획득할 기술: Data Warehousing, Data Management

      Intermediate · Course

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      Rice University

      Rice University

      Introduction to Data Analysis Using Excel

      획득할 기술: Pivot Table, Data Visualization, General Statistics, Business Analysis, Data Analysis Software, Statistical Visualization, Chart, Microsoft Excel, Data Mining, Analysis, Computer Programming, Spreadsheet Software, Data Analysis, Probability & Statistics

      4.7

      (9.4k개의 검토)

      Mixed · Course

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      University of Glasgow

      University of Glasgow

      Data mining of Clinical Databases - CDSS 1

      Intermediate · Course

    data mining과(와) 관련된 검색

    data mining project
    data mining foundations and practice
    data mining pipeline
    data mining methods
    data mining of clinical databases - cdss 1
    predictive analytics and data mining
    pattern discovery in data mining
    cluster analysis in data mining
    1234…15

    요약하자면, 여기에 가장 인기 있는 data mining 강좌 10개가 있습니다.

    • Data Mining: University of Illinois at Urbana-Champaign
    • Data Mining Foundations and Practice: University of Colorado Boulder
    • Applied Data Science with Python: University of Michigan
    • Introduction to Data Analysis using Microsoft Excel: Coursera Project Network
    • Google Data Analytics: Google
    • Data Mining Methods: University of Colorado Boulder
    • Predictive Analytics and Data Mining: University of Illinois at Urbana-Champaign
    • Pattern Discovery in Data Mining: University of Illinois at Urbana-Champaign
    • Cluster Analysis in Data Mining: University of Illinois at Urbana-Champaign
    • Data Mining Pipeline: University of Colorado Boulder

    Machine Learning에서 학습할 수 있는 스킬

    Python 프로그래밍 (33)
    TensorFlow (32)
    심층 학습 (30)
    인공 신경 회로망 (24)
    빅 데이터 (18)
    통계 분류 (17)
    강화 학습 (13)
    대수학 (10)
    베이지안 (10)
    선형 대수 (10)
    선형 회귀 (9)
    Numpy (9)

    데이터 마이닝에 대한 자주 묻는 질문

    • Data mining is the process of discovering meaningful patterns in large datasets to help guide an organization’s decision-making. With the use of techniques like regression, classification, and cluster analysis, data mining can sort through vast amounts of raw data to analyze customer preferences, detect fraudulent transactions, or perform social network analyses. Data mining is important because it delivers the descriptive and predictive analytics needed by an organization to increase productivity and sales, reduce costs, and prepare for the future.

      Like other areas of data science, data mining typically relies on the Python programming language for tasks like data cleansing, data organization, and machine learning (ML) applications. In social data mining, data clustering algorithms are used to inform recommender systems that can guide customers in entertainment and e-commerce choices. When delving into unstructured datasets, data mining can employ information retrieval (IR) and natural language processing (NLP) for text mining applications that can uncover customers’ emerging concerns or unmet needs.‎

    • Depending on the size of an organization, data mining specialists, data analysts, or data engineers may be responsible for data mining. Regardless of job title, data mining requires an understanding of all types of data, databases, and distributed file systems as well as statistical requirements for descriptive and predictive analysis. And, although most data mining is performed with either Python or R programming skills, knowledge of SQL and business intelligence software can also be very important.

      Data mining is also a core skill for data scientists, who have the programming skills, understanding of statistics, and ability to wrangle and visualize data that is essential in this field. They also have the in-depth knowledge of ML algorithms to aid their exploratory analysis, whether they are solving public policy questions, helping to detect disease outbreaks, or identifying money laundering operations. According to Glassdoor, the national average salary for a data scientist in the United States is $113,309 per year.‎

    • Yes! Coursera has a wide range of online courses and Specializations on data mining and related topics including machine learning, natural language processing, and applied data science with Python. You can take courses from top-ranked institutions like the University of Illinois at Urbana-Champaign, Johns Hopkins University, and the University of Washington, as well as industry-leading organizations like IBM, so you don’t have to sacrifice the quality of your education for the opportunity to learn online.

      Coursera also offers the opportunity to earn a Data Science Professional Certificate from IBM. And, with Coursera Guided Projects, you have the opportunity to add skills to your resume through hands-on tutorials presented by expert instructors in cutting-edge topics like Covid-19 data analysis using Python and sentiment analysis with deep learning.‎

    • The skills or experience you need to already have before starting to learn data mining might include a strong background in computer literacy and cloud technology skills, especially in programming software, data analysis, and business intelligence. Learning about data mining also involves using statistical methods and predictive models to create business solutions, so having experience and background in using statistical software would be helpful. Learning data mining does not require a college degree, but it would be beneficial to have an appropriate undergraduate degree in data science, computer science, information systems, business administration, or even statistics for working in the demanding field.‎

    • The kind of people who are best suited for work that involves data mining are disciplined programmers who are problem solvers, inquisitive explorers, and analytical self-starters. Working in data mining involves the practice of analyzing data to find and identify unforeseen patterns and possible system relationships that may be used to better understand future consumer behaviors. With this information, data miners can help transform this raw information into business insights for their senior leadership to make more and better-informed decisions.‎

    • To know if learning data mining might be right for you, you should be passionate about data analysis and have a focus on numbers, data, and how to create an understanding of various subsets of data. Data mining insiders may make data mining out to be extremely complex, but you may be able to learn the basic skills from online courses, online videos, websites, and web discussion forums. If you're interested in data sciences and how they may propel certain business decisions, then it may be a smart move to learn about data mining, as it’s part of the big data revolution occurring in our technological society and should hold promise for a future career.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
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