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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

    • Status: Free Trial
      Free Trial
      I

      IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Feature Engineering, Data Analysis, Data Cleansing, Exploratory Data Analysis, Data Science, Artificial Intelligence, Statistical Analysis, Data Transformation, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Machine Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.4K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Exploratory Data Analysis

      Skills you'll gain: Exploratory Data Analysis, Plot (Graphics), R Programming, Statistical Visualization, Data Visualization Software, Ggplot2, Dimensionality Reduction, Graphing, Data Analysis, Scatter Plots, Unsupervised Learning, Box Plots, Histogram, Statistical Methods

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Preview
      Preview
      U

      University of Leeds

      Exploratory Data Analysis

      Skills you'll gain: Exploratory Data Analysis, Data Literacy, Histogram, Data Analysis, Descriptive Statistics, Box Plots, Data Visualization, R Programming, Data Cleansing, Graphical Tools, Code Review

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis with Python

      Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Manipulation, Data Import/Export, Data Transformation, Predictive Modeling, Data Analysis, Data Cleansing, Regression Analysis, Pandas (Python Package), Data-Driven Decision-Making, Scikit Learn (Machine Learning Library), Statistical Analysis, Supervised Learning, Machine Learning Methods, Python Programming, NumPy, Data Visualization

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Web Scraping, Object Oriented Programming (OOP), Data Analysis, Python Programming, Pandas (Python Package), Data Collection, Data Structures, Data Manipulation, Programming Principles, NumPy, Application Programming Interface (API), Data Import/Export, File Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      42K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Illinois Urbana-Champaign

      Tools for Exploratory Data Analysis in Business

      Skills you'll gain: Data Presentation, Extract, Transform, Load, Exploratory Data Analysis, Business Analytics, Interactive Data Visualization, Alteryx, Business Intelligence, Data Storytelling, Power BI, Data Quality, Analytical Skills, Data Analysis, Data Visualization Software, Data Transformation, Data Processing, Data Manipulation, R Programming

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      51 reviews

      Beginner · Course · 1 - 4 Weeks

    What brings you to Coursera today?

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Generative AI for Data Analysis

      Skills you'll gain: Prompt Engineering, Data Ethics, Data Storytelling, Generative AI, Root Cause Analysis, Predictive Modeling, Data Visualization, Data Presentation, Interactive Data Visualization, Excel Formulas, Problem Management, Dashboard, Large Language Modeling, Anomaly Detection, Infographics, Data Visualization Software, Risk Analysis, Microsoft Copilot, Predictive Analytics, Automation

      4.3
      Rating, 4.3 out of 5 stars
      ·
      81 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to Data Analytics

      Skills you'll gain: Data Storytelling, Data Presentation, Data Visualization, Extract, Transform, Load, Data Visualization Software, Data Analysis, Statistical Analysis, Big Data, Data Wrangling, Data Mining, Analytics, Data Warehousing, Business Analytics, Data Science, Data Cleansing, Data Lakes, Data Modeling, Data Transformation, Microsoft Excel

      4.8
      Rating, 4.8 out of 5 stars
      ·
      19K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Perform exploratory data analysis on retail data with Python

      Skills you'll gain: Data Visualization, Exploratory Data Analysis, Anomaly Detection, Data Analysis, Data Cleansing, Customer Analysis, Trend Analysis, Statistical Analysis, Pandas (Python Package), Data Manipulation, Matplotlib, Data Transformation, Jupyter, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      Exploratory Data Analysis With Python and Pandas

      Skills you'll gain: Exploratory Data Analysis, Correlation Analysis, Pandas (Python Package), Seaborn, Matplotlib, Data Visualization, Data Cleansing, Data Analysis, Statistical Analysis, NumPy, Descriptive Statistics, Data Manipulation, Python Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      438 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      G

      Google

      Google Advanced Data Analytics

      Skills you'll gain: Data Storytelling, Exploratory Data Analysis, Sampling (Statistics), Statistical Hypothesis Testing, Regression Analysis, Statistical Analysis, Data Ethics, Statistics, Unsupervised Learning, Data Presentation, Data Visualization Software, Data Visualization, Data Analysis, Machine Learning, Data Manipulation, Data Science, Tableau Software, Interviewing Skills, Python Programming, Advanced Analytics

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.7K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      I

      IBM

      IBM Data Science

      Skills you'll gain: Data Wrangling, SQL, Unsupervised Learning, Exploratory Data Analysis, Matplotlib, Supervised Learning, Data Literacy, Relational Databases, Data Manipulation, Applied Machine Learning, Data Import/Export, Data Visualization Software, Professional Networking, Predictive Modeling, Plotly, Dashboard, Generative AI, Jupyter, Data Science, Web Scraping

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      146K reviews

      Beginner · Professional Certificate · 3 - 6 Months

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

    • Exploratory Data Analysis for Machine Learning: IBM
    • Exploratory Data Analysis: Johns Hopkins University
    • Exploratory Data Analysis: University of Leeds
    • Data Analysis with Python: IBM
    • Python for Data Science, AI & Development: IBM
    • Tools for Exploratory Data Analysis in Business: University of Illinois Urbana-Champaign
    • Microsoft Generative AI for Data Analysis: Microsoft
    • Introduction to Data Analytics: IBM
    • Perform exploratory data analysis on retail data with Python: Coursera Project Network
    • Exploratory Data Analysis With Python and Pandas: Coursera Project Network

    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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