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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

    • U

      University of Pennsylvania

      Data Analysis Using Python

      Skills you'll gain: Matplotlib, Data Analysis, Pandas (Python Package), Data Cleansing, Pivot Tables And Charts, Data Visualization Software, Data Manipulation, Scatter Plots, NumPy, Data Transformation, Jupyter, Data Validation, Data Import/Export, Histogram, Data Structures, Programming Principles, Scripting Languages

      4.5
      Rating, 4.5 out of 5 stars
      ·
      416 reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      PwC

      Data-driven Decision Making

      Skills you'll gain: Analytics, Business Analytics, Data Analysis, Data-Driven Decision-Making, Business Intelligence, Data Literacy, Big Data, Data Storytelling, Statistical Analysis, Microsoft Excel, Data Visualization Software, R Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Microsoft

      Preparing Data for Analysis with Microsoft Excel

      Skills you'll gain: Excel Formulas, Microsoft Excel, Spreadsheet Software, Power BI, Data Analysis, Productivity Software, Data Cleansing, Data Manipulation, Data Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Wrangling, Data Visualization, Plot (Graphics), Statistical Programming, Ggplot2, Big Data, Git (Version Control System), Data Integration, Knitr, Data Analysis, Data Sharing, Statistical Reporting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      48K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado System

      Data Warehousing for Business Intelligence

      Skills you'll gain: Database Design, Data Warehousing, Relational Databases, Decision Support Systems, Business Intelligence, Data Modeling, Database Management Systems, Databases, Dashboard, Business Process Management, SQL, Star Schema, Data Governance, Data Integration, Oracle Databases, Performance Measurement, Extract, Transform, Load, Business Analytics, MicroStrategy, Data Visualization Software

      4.5
      Rating, 4.5 out of 5 stars
      ·
      4.1K reviews

      Advanced · Specialization · 3 - 6 Months

    • G

      Google

      Analyze Data to Answer Questions

      Skills you'll gain: Data Validation, Spreadsheet Software, Data Analysis, Analytics, Data Manipulation, Excel Formulas, Data Compilation, Pivot Tables And Charts, SQL, Data Integration, Data Transformation, User Feedback

      4.6
      Rating, 4.6 out of 5 stars
      ·
      12K reviews

      Beginner · Course · 1 - 4 Weeks

    • M

      Macquarie University

      Excel Fundamentals for Data Analysis

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Manipulation, Spreadsheet Software, Data Transformation, Data Validation, Data Analysis, Pivot Tables And Charts, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.1K reviews

      Intermediate · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Introduction to Systematic Review and Meta-Analysis

      Skills you'll gain: Clinical Trials, Clinical Research, Qualitative Research, Data Synthesis, Scientific Methods, Research Methodologies, Data Collection, Biostatistics, Analysis, Quantitative Research, Risk Analysis, Statistical Methods, Epidemiology, Statistical Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.5K reviews

      Mixed · Course · 1 - 3 Months

    • Status: New
      New
      I

      IBM

      IBM Data Architecture

      Skills you'll gain: NoSQL, Data Warehousing, SQL, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Data Security, Linux Commands, Data Migration, Database Design, Data Governance, MySQL, Apache Spark, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Store

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.5K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Data Warehouse Engineer

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Linux Commands, Database Design, IBM Cognos Analytics, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Store, IBM DB2, Relational Databases, Dashboard, File Management, Stored Procedure

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • G

      Google

      Google Data Analytics Capstone: Complete a Case Study

      Skills you'll gain: Interviewing Skills, Data Analysis, Google Analytics, Data Processing, Analytical Skills, Artificial Intelligence, R Programming, Data Storytelling, Project Documentation, Presentations, Portfolio Management, LinkedIn

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18K reviews

      Beginner · Course · 1 - 4 Weeks

    • R

      Rice University

      Introduction to Data Analysis Using Excel

      Skills you'll gain: Microsoft Excel, Pivot Tables And Charts, Graphing, Spreadsheet Software, Excel Formulas, Data Analysis, Histogram, Scatter Plots, Data Manipulation, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      10K reviews

      Mixed · Course · 1 - 4 Weeks

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

    • Data Analysis Using Python: University of Pennsylvania
    • Data-driven Decision Making: PwC
    • Preparing Data for Analysis with Microsoft Excel: Microsoft
    • Data Science: Foundations using R: Johns Hopkins University
    • Data Warehousing for Business Intelligence: University of Colorado System
    • Analyze Data to Answer Questions: Google
    • Excel Fundamentals for Data Analysis: Macquarie University
    • Introduction to Systematic Review and Meta-Analysis: Johns Hopkins University
    • IBM Data Architecture: IBM
    • IBM Data Warehouse Engineer: IBM

    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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