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    • Data Mining

    Data Mining Courses Online

    Understand data mining principles for discovering patterns in large datasets. Learn to use machine learning algorithms for predictive analysis.

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    Explore the Data Mining Course Catalog

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Extract, Transform and Load Data in Power BI

      Skills you'll gain: Extract, Transform, Load, Power BI, Data Validation, Data Transformation, Data Cleansing, Data Storage, Data Quality, Data Analysis, Data Integration, Data Storage Technologies, Business Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      868 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Washington

      Computational Neuroscience

      Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Mathematical Modeling, Biology, Linear Algebra, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Understanding and Visualizing Data with Python

      Skills you'll gain: Sampling (Statistics), Data Visualization, Statistics, Matplotlib, Statistical Visualization, Probability & Statistics, Jupyter, Statistical Methods, Data Visualization Software, Data Analysis, Statistical Analysis, Exploratory Data Analysis, Descriptive Statistics, Statistical Inference, Data Collection, NumPy, Histogram, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Instructor Network

      Data Privacy and Protection Standards

      Skills you'll gain: Information Privacy, General Data Protection Regulation (GDPR), Personally Identifiable Information, Data Security, Data Governance, Data Ethics, Data Loss Prevention, Security Controls, Regulatory Compliance, Compliance Management, Data Integrity, Security Strategy, Incident Response

      4.8
      Rating, 4.8 out of 5 stars
      ·
      28 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Fundamentals of Data Visualization

      Skills you'll gain: Data Visualization Software, Interactive Data Visualization, Visualization (Computer Graphics), User Centered Design, Statistical Visualization, Data Presentation, Usability, Data Storytelling, Human Computer Interaction, User Research, Usability Testing, Requirements Analysis, Design Elements And Principles

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      36 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      P

      Princeton University

      Algorithms, Part II

      Skills you'll gain: Graph Theory, Data Structures, Algorithms, Theoretical Computer Science, Operations Research, Computational Thinking, Computer Programming, Network Routing, Programming Principles, Network Model, Java Programming

      4.9
      Rating, 4.9 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      From Data to Insights with Google Cloud

      Skills you'll gain: Looker (Software), Dashboard, SQL, Data Transformation, Big Data, Google Cloud Platform, Applied Machine Learning, Data Cleansing, Machine Learning, Cloud Infrastructure, Data Import/Export, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Data Access, Data Warehousing, Supervised Learning, Database Architecture and Administration, Data Visualization Software, Predictive Modeling, Deep Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Azure AI Fundamentals AI-900 Exam Prep

      Skills you'll gain: Anomaly Detection, Image Analysis, Text Mining, Unsupervised Learning, Computer Vision, Artificial Intelligence, Natural Language Processing, Microsoft Azure, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Large Language Modeling, Regression Analysis, Predictive Modeling, Machine Learning Methods, Statistical Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Automation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Data Visualization and Communication with Tableau

      Skills you'll gain: Data Storytelling, Dashboard, Tableau Software, Data Visualization, Business Analytics, Statistical Visualization, Business Process, Business Process Improvement, Presentations, Data Visualization Software, Data-Driven Decision-Making, Data Analysis, Graphing, Stakeholder Communications, Data Manipulation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.2K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Architecting with Google Kubernetes Engine

      Skills you'll gain: Kubernetes, Identity and Access Management, Cloud-Native Computing, Google Cloud Platform, CI/CD, Containerization, Application Deployment, Cloud Management, Scalability, Cloud Computing, Cloud Infrastructure, Load Balancing, Continuous Integration, DevOps, Continuous Delivery, YAML, Data Storage, Cloud Security, Cloud Services, Application Performance Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.1K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Natural Language Processing with Probabilistic Models

      Skills you'll gain: Natural Language Processing, Markov Model, Text Mining, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Machine Learning Methods, Data Processing, Algorithms, Data Cleansing, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Generative AI Engineering with LLMs

      Skills you'll gain: Prompt Engineering, Large Language Modeling, Generative AI, Natural Language Processing, Generative AI Agents, PyTorch (Machine Learning Library), Text Mining, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Deep Learning, Application Development, Artificial Intelligence, Feature Engineering, Document Management, Machine Learning Methods, Jupyter, Data Processing, Applied Machine Learning, Performance Tuning, Application Frameworks

      4.5
      Rating, 4.5 out of 5 stars
      ·
      430 reviews

      Intermediate · Specialization · 3 - 6 Months

    Data Mining learners also search

    Data
    R
    Data Science
    Data Analytics
    Data Analysis
    R Programming
    Applied Data Science
    Beginner Data Science
    1…414243…604

    In summary, here are 10 of our most popular data mining courses

    • Extract, Transform and Load Data in Power BI: Microsoft
    • Computational Neuroscience: University of Washington
    • Understanding and Visualizing Data with Python: University of Michigan
    • Data Privacy and Protection Standards: Coursera Instructor Network
    • Fundamentals of Data Visualization: University of Colorado Boulder
    • Algorithms, Part II: Princeton University
    • From Data to Insights with Google Cloud: Google Cloud
    • Microsoft Azure AI Fundamentals AI-900 Exam Prep: Microsoft
    • Data Visualization and Communication with Tableau: Duke University
    • Architecting with Google Kubernetes Engine: Google Cloud

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Data Mining

    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.‎

    Online Data Mining courses offer a convenient and flexible way to enhance your knowledge or learn new Data Mining skills. Choose from a wide range of Data Mining courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Data Mining, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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