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    • Exploratory Data Analysis

    Exploratory Data Analysis Courses Online

    Learn exploratory data analysis (EDA) for uncovering patterns and insights. Understand data visualization, summary statistics, and hypothesis testing.

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    Explore the Exploratory Data Analysis Course Catalog

    • G

      Google Cloud

      Introduction to Gemini for Google Workspace - Indonesian

      Skills you'll gain: Google Workspace, Generative AI, Data Ethics, Artificial Intelligence, Gmail, Prompt Engineering

      Beginner · Course · 1 - 4 Weeks

    • I

      Illinois Institute of Technology

      Master of Data Science

      Skills you'll gain:

      Earn a degree

      Degree · 1 - 4 Years

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Relational Database Design and Advanced Querying

      Skills you'll gain:

      Beginner · Course

    • G

      Google Cloud

      Responsible AI: Interpretability & Transparency - Deutsch

      Skills you'll gain: Data Ethics, Data Analysis, Data Science, Analysis, Applied Machine Learning, Data Visualization Software, Artificial Intelligence, Machine Learning, Technical Communication

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Boost Productivity with Gemini in BigQuery - Português

      Skills you'll gain: Data Processing, Data Analysis, Google Cloud Platform, Big Data, Data-Driven Decision-Making, Data Cleansing, Data Manipulation, Artificial Intelligence, Generative AI, Interactive Data Visualization, SQL, Problem Management

      Beginner · Course · 1 - 4 Weeks

    • P

      Pontificia Universidad Católica de Chile

      Certificado en Introducción a la Ciencia de Datos

      Skills you'll gain: Predictive Analytics, Unsupervised Learning, Data Cleansing, Exploratory Data Analysis, Data Visualization, Dimensionality Reduction, Data Science, Descriptive Analytics, Supervised Learning, Regression Analysis, Scientific Visualization, Data-Driven Decision-Making, Data Processing, Time Series Analysis and Forecasting, Pandas (Python Package), Data Visualization Software, Statistical Machine Learning, Data Manipulation, Statistical Visualization, Machine Learning

      Credit offered

      Mastertrack · 6 - 12 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Indexing, Performance Optimization & Functions in SQL Server

      Skills you'll gain:

      Beginner · Course

    • U

      University of Pittsburgh

      Master of Data Science

      Skills you'll gain:

      Earn a degree

      Degree · 1 - 4 Years

    • P

      Pontificia Universidad Católica de Chile

      Magíster en Ciencia de Datos

      Skills you'll gain: Revenue Management, Data Ethics, Customer Analysis, Descriptive Analytics, FinTech, Database Design, People Analytics, Time Series Analysis and Forecasting, Biostatistics, Predictive Analytics, Statistical Reporting, Unsupervised Learning, Digital Transformation, Deep Learning, Risk Analysis, Bayesian Statistics, Exploratory Data Analysis, Cloud Security, Network Model, Data Visualization

      Earn a degree

      Degree · 1 - 4 Years

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Security, Maintenance & Integration with BI Tools

      Skills you'll gain:

      Beginner · Course

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 繁體中文

      Skills you'll gain: Generative AI, Google Cloud Platform, Big Data, Customer Relationship Management, SQL, Business Modeling, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Natural Language Processing

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Interpretability & Transparency - 한국어

      Skills you'll gain: Data Ethics, Artificial Intelligence, Applied Machine Learning, Data Analysis, Data Visualization Software, Exploratory Data Analysis, Machine Learning, Technical Documentation, Software Documentation

      Intermediate · Course · 1 - 4 Weeks

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

    • Introduction to Gemini for Google Workspace - Indonesian: Google Cloud
    • Master of Data Science: Illinois Institute of Technology
    • Relational Database Design and Advanced Querying: Microsoft
    • Responsible AI: Interpretability & Transparency - Deutsch: Google Cloud
    • Boost Productivity with Gemini in BigQuery - Português: Google Cloud
    • Certificado en Introducción a la Ciencia de Datos: Pontificia Universidad Católica de Chile
    • Indexing, Performance Optimization & Functions in SQL Server: Microsoft
    • Master of Data Science: University of Pittsburgh
    • Magíster en Ciencia de Datos: Pontificia Universidad Católica de Chile
    • Security, Maintenance & Integration with BI Tools: Microsoft

    Skills you can learn in Probability And Statistics

    R Programming (19)
    Inference (16)
    Linear Regression (12)
    Statistical Analysis (12)
    Statistical Inference (11)
    Regression Analysis (10)
    Biostatistics (9)
    Bayesian (7)
    Logistic Regression (7)
    Probability Distribution (7)
    Bayesian Statistics (6)
    Medical Statistics (6)

    Frequently Asked Questions about Exploratory Data Analysis

    Exploratory data analysis (EDA) is an approach to data analysis used to investigate sets of data, summarize their characteristics, and figure out how to best work with data to get answers while providing a visual to help businesses, scientists, researchers, and analysts learn more from that data. Exploratory data analysis makes it easier to find patterns and anomalies in data, and it can be used to determine what the data reveals beyond modeling. It's useful as a step in creating sophisticated data models and analysis. EDA tools include clustering/dimension reduction techniques to create graphs, K-means clustering, and predictive modeling, including linear regression. There are four main types of exploratory data analysis, including univariate non-graphical, univariate graphical, multivariate nongraphical, and multivariate graphical. All of these types describe the data, but graphical exploratory data analysis provides a more complete picture created by the data.‎

    If you're passionate about working with numbers and transforming them to tell a story that influences others, learning about exploratory data analysis can help you forge a career based on that passion. It's a solid start to jobs in data science, but you'll also gain a variety of related skills, including coding using Python and R, data cleansing, and predictive modeling. Beyond starting a new career or advancing your existing one, there are benefits for anyone who chooses to learn about exploratory data analysis, including solid problem-solving skills, the ability to find connections between data and real-world problems, and gaining useful tools to guide major decisions ranging from getting the most out of marketing campaigns to maximizing project executions to hiring key players for organizations.‎

    If you're looking for a career in transforming large volumes of data into actionable advice and solutions, a career in exploratory data analytics could be your ideal path, particularly if you're passionate about using data to evaluate whether the statistical methods you intend to use for analyzing that data are the most effective options. This fast-growing field is in-demand, with skilled, knowledgeable exploratory data analysts among the most highly sought professionals across multiple industries. Exploratory data analysis is somewhat like solving puzzles, piecing data-driven insights together to help employers and clients make well-informed business decisions based on sound data that's been evaluated for assumptions, errors, and trends. You might work on Wall Street for a hedge fund or investment bank. You could work in healthcare, insurance, retail, or marketing, among other industries.‎

    Online courses on Coursera give you the opportunity to do everything from gaining experience in fundamentals to earning professional certification. If you're new to the field, beginner courses like Exploratory Data Analysis with MATLAB can help you build a foundation in data analysis and data visualization. If you're looking to advance your skills, you might explore your options to gain professional certification through IBM's IBM Data Analyst offering. Or you could opt for a specialization, like the Data Science option from Johns Hopkins, which combines courses and applied learning to help you build firsthand knowledge and skills that you'll be able to apply in business settings.‎

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

    When looking to enhance your workforce's skills in Exploratory Data Analysis, 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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