What is data mining, and why is it important to learn about?

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.

What kinds of careers can I have with a background in data mining?

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.

Can I learn about data mining by taking online courses on Coursera?

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.

What skills or experience do I need to already have, before starting to learn data mining?

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.

What kind of people are best suited for roles that involve data mining?

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.

How do I know if learning data mining is right for me?

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.

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「data mining」の361件の結果

University of Illinois at Urbana-Champaign
Data Mining
習得できるスキル： Machine Learning, Data Analysis, Data Mining, Natural Language Processing, Machine Learning Algorithms, Data Science, Data Visualization, Probability & Statistics, Python Programming, Statistical Programming, Bayesian Statistics, C Programming Language Family, Computer Programming, Algorithms, Applied Machine Learning, Bioinformatics, Business Psychology, Calculus, Computer Graphics, Data Management, Data Structures, Entrepreneurship, General Statistics, Geovisualization, Mathematics, Network Analysis, Project Management, Spatial Data Analysis, Statistical Analysis, Strategy and Operations, Theoretical Computer Science
4.5
（2.8k件のレビュー）
Intermediate · Specialization · 3-6 Months
IBM Skills Network
IBM Data Science
習得できるスキル： Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Statistical Visualization, Database Application, Extract, Transform, Load, Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Computer Programming, Database Administration, Geovisualization, Plot (Graphics), Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing
4.6
（106k件のレビュー）
Beginner · Professional Certificate · 3-6 Months
Google
Google Data Analytics
習得できるスキル： Data Analysis, Statistical Programming, Data Science, Business Analysis, SQL, Spreadsheet Software, Data Visualization, Business, Data Management, Data Visualization Software, R Programming, Leadership and Management, Exploratory Data Analysis, Statistical Visualization, Change Management, Strategy and Operations, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Tableau Software, Big Data, Cloud Computing, Critical Thinking, Customer Analysis, General Statistics, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development
4.8
（101.2k件のレビュー）
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
Advanced Data Science with IBM
習得できるスキル： Machine Learning, Data Management, Statistical Programming, Python Programming, Machine Learning Algorithms, Apache, Deep Learning, Machine Learning Software, Artificial Neural Networks, Probability & Statistics, Cloud Computing, Statistical Machine Learning, Extract, Transform, Load, Basic Descriptive Statistics, General Statistics, IBM Cloud, Data Model, Applied Machine Learning, Data Analysis, Data Visualization, Dimensionality Reduction, SQL, Statistical Visualization, Feature Engineering, Linear Algebra, Mathematics, Natural Language Processing, Tensorflow, Bayesian Network, Cloud Platforms, Cloud Storage, Computer Vision, Correlation And Dependence, Data Structures, Data Warehousing, Database Application, NoSQL, Plot (Graphics), Probability Distribution, R Programming, Regression, Algorithms, Bayesian Statistics, Big Data, Change Management, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis Software, Data Mining, Distributed Computing Architecture, Estimation, Exploratory Data Analysis, Internet Of Things, Leadership and Management, Programming Principles, Statistical Analysis, Strategy and Operations, Theoretical Computer Science
4.3
（2.9k件のレビュー）
Advanced · Specialization · 3-6 Months
University of Pennsylvania
Business Analytics
習得できるスキル： Business Analysis, Data Analysis, Probability & Statistics, Statistical Analysis, General Statistics, Research and Design, Forecasting, Strategy and Operations, Correlation And Dependence, Financial Analysis, Accounting, Human Resources, Marketing, Operational Analysis, Operations Management, Operations Research, Probability Distribution, Spreadsheet Software, Supply Chain and Logistics, Customer Analysis, Financial Accounting, Market Analysis, Market Research, Basic Descriptive Statistics, Exploratory Data Analysis, Finance, People Management, Performance Management, Regulations and Compliance, Statistical Tests, Talent Management, Collaboration, Communication, Critical Thinking, Data Management, Data Mining, Data Model, Data Visualization, Generally Accepted Accounting Principles (GAAP), HR Tech, Leadership Development, Leadership and Management, MarTech, Marketing Management, Media Strategy & Planning, Microsoft Excel, Organizational Development, Plot (Graphics), Process Analysis, Recruitment, Statistical Programming, Statistical Visualization, Applied Mathematics, Big Data, Business Psychology, Computational Logic, Computer Programming, Computer Programming Tools, Data Analysis Software, Data Structures, Decision Making, Entrepreneurship, Estimation, Mathematics, Network Analysis, People Analysis, People Development, Regression, Sales, Strategy, Theoretical Computer Science
4.6
（17.1k件のレビュー）
Beginner · Specialization · 3-6 Months
無料
Eindhoven University of Technology
Process Mining: Data science in Action
習得できるスキル： Business Analysis, Process Analysis, Data Analysis, Data Mining, Machine Learning, Machine Learning Algorithms, Algorithms, Business Process Management, Business Psychology, Communication, Data Management, Data Structures, Entrepreneurship, Leadership and Management, Organizational Development, Strategy and Operations, Theoretical Computer Science
4.7
（1.1k件のレビュー）
Intermediate · Course · 1-3 Months
IBM Skills Network
Introduction to Data Science
習得できるスキル： Data Science, Data Structures, SQL, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Statistical Programming, Databases, Python Programming, Database Theory, Data Visualization Software, R Programming, Data Management, Data Mining, Database Application, Regression, Devops Tools, Machine Learning Algorithms, SPSS, Basic Descriptive Statistics, Data Analysis, Database Administration, Big Data, Computer Programming, Deep Learning, General Statistics, Machine Learning, Marketing, Probability & Statistics, Storytelling, Writing
4.6
（77k件のレビュー）
Beginner · Specialization · 3-6 Months
University of Pennsylvania
AI For Business
習得できるスキル： Machine Learning, Entrepreneurship, Leadership and Management, Strategy and Operations, Machine Learning Algorithms, Finance, Data Management, Theoretical Computer Science, Applied Machine Learning, Business Analysis, Human Resources, Marketing, Artificial Neural Networks, Deep Learning, Computational Thinking, Computer Programming, Data Analysis, Accounting, Algorithms, People Management, Regulations and Compliance, Sales, Big Data, Data Mining, Data Warehousing, Feature Engineering, Natural Language Processing, Reinforcement Learning, Audit, BlockChain, Business Transformation, Clinical Data Management, Customer Analysis, Customer Relationship Management, Customer Success, Database Administration, Databases, Decision Making, Financial Analysis, Innovation, Research and Design, Security Engineering, Software Security, Strategy
4.6
（121件のレビュー）
Beginner · Specialization · 3-6 Months
Stanford University
AI in Healthcare
習得できるスキル： Machine Learning, Applied Machine Learning, Data Management, Finance, Leadership and Management, Clinical Data Management, Data Analysis, Data Mining, Deep Learning, Machine Learning Algorithms, Payments, Regulations and Compliance, Risk Management, Accounting, Marketing
4.7
（989件のレビュー）
Beginner · Specialization · 3-6 Months
DeepLearning.AI
Natural Language Processing
習得できるスキル： Machine Learning, Natural Language Processing, Statistical Programming, Python Programming, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Data Science, Statistical Machine Learning, Probability & Statistics, Algorithms, Bayesian Statistics, Communication, Computer Graphics, Computer Programming, Dimensionality Reduction, Experiment, General Statistics, Human Computer Interaction, Machine Learning Software, Markov Model, Mathematics, Operations Research, Regression, Research and Design, Strategy and Operations, Theoretical Computer Science, User Experience
4.6
（4.9k件のレビュー）
Intermediate · Specialization · 3-6 Months

data miningに関連する検索

data mining foundations and practice

data mining methods

data mining pipeline

data mining project

data mining of clinical databases - cdss 1

data mining for smart cities

predictive analytics and data mining

cluster analysis in data mining

要約して、data mining の人気コース10選をご紹介します。

Data Mining: University of Illinois at Urbana-Champaign
Data Mining Foundations and Practice: University of Colorado Boulder
IBM Data Science: IBM Skills Network
Google Data Analytics: Google
Advanced Data Science with IBM: IBM Skills Network
Business Analytics: University of Pennsylvania
Process Mining: Data science in Action: Eindhoven University of Technology
Data Mining Project: University of Colorado Boulder
Introduction to Data Science: IBM Skills Network
AI For Business: University of Pennsylvania

Machine Learningで学べるスキル

データマイニングに関するよくある質問

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.‎