Kompetenzen, die Sie erwerben: 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
Intermediate · Course · 1-3 Months
Kompetenzen, die Sie erwerben: Business Analysis, Data Analysis, Data Management, Probability & Statistics, Big Data, Data Mining, Data Structures, Statistical Analysis, Theoretical Computer Science, Advertising, Communication
Intermediate · Course · 1-4 Weeks
Kompetenzen, die Sie erwerben: Machine Learning, Machine Learning Algorithms, Python Programming, Statistical Programming, Algorithms, Calculus, Data Analysis, Data Mining, Mathematics, Natural Language Processing, Theoretical Computer Science
Mixed · Course · 1-3 Months
Kompetenzen, die Sie erwerben: Data Analysis, Data Mining, Machine Learning, Machine Learning Algorithms, Algorithms, Applied Machine Learning, Probability & Statistics, Spatial Data Analysis, Statistical Analysis, Theoretical Computer Science
Mixed · Course · 1-3 Months
Kompetenzen, die Sie erwerben: Algorithms, Business Psychology, Computer Graphics, Computer Programming, Data Analysis, Data Mining, Data Visualization, Entrepreneurship, General Statistics, Geovisualization, Machine Learning, Natural Language Processing, Probability & Statistics, Project Management, Python Programming, Statistical Programming, Strategy and Operations, Theoretical Computer Science
Mixed · Course · 1-3 Months
Kompetenzen, die Sie erwerben: Data Analysis, Python Programming, Data Visualization, Exploratory Data Analysis, Basic Descriptive Statistics, Data Structures, Statistical Programming, Data Science, Statistical Visualization, Plot (Graphics), Data Management, General Statistics, SQL, Databases, Business Analysis, Microsoft Excel, Spreadsheet Software, Data Mining, Statistical Analysis, Programming Principles, Probability & Statistics, Regression, Machine Learning, Algebra, Computer Programming, Data Analysis Software, Database Theory, Probability Distribution, Applied Machine Learning, Statistical Tests, Big Data, Correlation And Dependence, Data Visualization Software, Estimation, NoSQL, Geovisualization, ArcGIS, Cloud Computing, Data Warehousing, Database Application, Extract, Transform, Load, HTML and CSS, Knitr, Mathematics, Minitab, PostgreSQL, R Programming, SAS (Software), SPSS, Apache, Computational Logic, Computer Programming Tools, Database Administration, Econometrics, Interactive Data Visualization, Leadership and Management, Mathematical Theory & Analysis, Operating Systems, Professional Development, Statistical Machine Learning, System Programming, Theoretical Computer Science
Beginner · Professional Certificate · 3-6 Months
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.