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.

Обзор
Data Mining

Фильтр

Результатов для запроса ''data mining': 194

University of Illinois at Urbana-Champaign
Data Mining
Получаемые навыки: Algorithms, Applied Machine Learning, Bayesian Statistics, Bioinformatics, Business Psychology, Calculus, Computer Graphics, Computer Programming, Data Analysis, Data Management, Data Mining, Data Structures, Data Visualization, Databases, Documents, Entrepreneurship, General Statistics, Geovisualization, Machine Learning, Machine Learning Algorithms, Mathematics, Natural Language Processing, Probability & Statistics, Project Management, Python Programming, Recommender Systems, SQL, Software, Statistical Programming, Strategy and Operations, Theoretical Computer Science
4.5
(рецензий: 2.7k)
Intermediate · Specialization · 3-6 Months
Google
Google Data Analytics
Получаемые навыки: Algorithms, Application Development, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Structures, Data Validation, Data Visualization, Data Visualization Software, 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, General Statistics, Interactive Data Visualization, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Plot (Graphics), Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software Engineering, Software Security, Spreadsheet, Spreadsheet Software, Statistical Analysis, Statistical Programming, Storytelling, Strategy and Operations, Tableau Software, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development
4.8
(рецензий: 77.9k)
Beginner · Professional Certificate · 3-6 Months
University of Michigan
Applied Data Science with Python
Получаемые навыки: Algorithms, Applied Machine Learning, Artificial Neural Networks, Computational Logic, Computer Graphics, Computer Networking, Computer Programming, Data Analysis, Data Mining, Data Visualization, Econometrics, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Mathematical Theory & Analysis, Mathematics, Modeling, Natural Language, Natural Language Processing, Network Analysis, Network Model, Plot (Graphics), Probability & Statistics, Programming Principles, Python Programming, Regression, Statistical Machine Learning, Statistical Programming, Statistical Tests, Theoretical Computer Science
4.5
(рецензий: 32.3k)
Intermediate · Specialization · 3-6 Months
DeepLearning.AI, Stanford University
Machine Learning
Получаемые навыки: Accounting, Algorithms, Applied Machine Learning, Artificial Neural Networks, Bayesian Statistics, Calculus, Communication, Computer Programming, Computer Vision, Data Analysis, Data Management, Data Mining, Data Structures, Deep Learning, Econometrics, Feature Engineering, General Statistics, Linear Algebra, Logistic Regression, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Operations Research, Probability & Statistics, Probability Distribution, Python Programming, Regression, Reinforcement Learning, Research and Design, Statistical Classification, Statistical Machine Learning, Statistical Programming, Strategy and Operations, Tensorflow, Theoretical Computer Science
4.9
(рецензий: 3.7k)
Beginner · Specialization · 1-3 Months
Бесплатно
Eindhoven University of Technology
Process Mining: Data science in Action
Получаемые навыки: Theoretical Computer Science, Data Analysis, Data Structures, Machine Learning Algorithms, Data Mining, Machine Learning, Data Management, Entrepreneurship, Organizational Development, Leadership and Management, Strategy and Operations, Process Analysis, Business Analysis, Business Process Management, Business Psychology, Modeling, Algorithms, Communication, Process
4.7
(рецензий: 1.1k)
Intermediate · Course · 1-3 Months
IBM Skills Network
Data Analysis with Python
Получаемые навыки: Data Analysis, Computer Programming Tools, Correlation And Dependence, Computer Programming, Machine Learning, Exploratory Data Analysis, Data Mining, Mathematical Theory & Analysis, Econometrics, General Statistics, Regression, Python Programming, Probability & Statistics, Spreadsheet Software, Statistical Programming, Statistical Analysis, Statistical Machine Learning, Linearity, Analysis, Regression Analysis, Modeling, Linear Regression, Algebra, Business Analysis
4.7
(рецензий: 15.5k)
Beginner · Course · 1-3 Months
IBM Skills Network
Ciencia de Datos de IBM
Получаемые навыки: Algorithms, Computer Programming, Data Analysis, Data Management, Data Mining, Data Model, Data Visualization, Databases, Econometrics, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, Probability & Statistics, Python Programming, R Programming, Regression, SQL, Statistical Programming, Theoretical Computer Science
4.6
(рецензий: 425)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
Introduction to Data Science
Получаемые навыки: Analysis, Communication, Computer Programming, Data Analysis, Data Management, Data Mining, Database Administration, Database Application, Databases, General Statistics, Machine Learning, Marketing, Modeling, Probability & Statistics, Python Programming, R Programming, Regression, SPSS, SQL, Statistical Programming
4.6
(рецензий: 72k)
Beginner · Specialization · 3-6 Months
University of Illinois at Urbana-Champaign
Predictive Analytics and Data Mining
Получаемые навыки: Theoretical Computer Science, Entrepreneurship, Mathematics, Econometrics, Marketing, Data Analysis, Market Research, Research and Design, Probability & Statistics, Data Clustering Algorithms, Analysis, Accounting, Bayesian Statistics, Advertising, Algorithms, Communication, Decision Tree, Algebra, Predictive Analytics, Analytics
4.4
(рецензий: 127)
Intermediate · Course · 1-4 Weeks

Результаты поиска, связанного с data mining

data mining foundations and practice

data mining project

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

10 самых популярных курсов по запросу data mining

Data Mining: University of Illinois at Urbana-Champaign
Data Mining Foundations and Practice: University of Colorado Boulder
Google Data Analytics: Google
Applied Data Science with Python: University of Michigan
Data Mining Methods: University of Colorado Boulder
Machine Learning: DeepLearning.AI
Process Mining: Data science in Action: Eindhoven University of Technology
Data Analysis with Python: IBM Skills Network
Data Mining Project: University of Colorado Boulder
Ciencia de Datos de IBM: IBM Skills Network

Навыки, которые вы можете получить здесь: Machine Learning

Программирование На Языке Python (33)

TensorFlow (32)

Глубокое Обучение (30)

Искусственная Нейронная Сеть (24)

Большие Данные (18)

Статистическая Классификация (17)

Обучения С Подкреплением (13)

Алгебра (10)

Байесовский (10)

Линейная Алгебра (10)

Линейная Регрессия (9)

NumPy (9)

Часто задаваемые вопросы на тему Интеллектуальный анализ данных

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.‎

Часто задаваемые вопросы предоставляются в ознакомительных целях. Учащимся рекомендуется дополнительно убедиться в том, что интересующие их курсы и другие материалы соответствуют их личным, профессиональным и финансовым потребностям.