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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

    • I

      IBM

      Data Engineering Foundations

      Skills you'll gain: Web Scraping, Database Design, SQL, MySQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Jupyter, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Manipulation, Stored Procedure, Databases, Automation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

    • F

      Fractal Analytics

      Data Analysis Using SQL

      Skills you'll gain: Database Design, Data Manipulation, SQL, Relational Databases, Database Management, Data Analysis, Data Cleansing, Databases, Query Languages, Data Transformation, Data Integrity

      4.4
      Rating, 4.4 out of 5 stars
      ·
      41 reviews

      Beginner · Course · 1 - 3 Months

    • M

      Macquarie University

      Excel Power Tools for Data Analysis

      Skills you'll gain: Power BI, Data Analysis Expressions (DAX), Data Visualization Software, Data Modeling, Microsoft Excel, Interactive Data Visualization, Pivot Tables And Charts, Data Transformation, Dashboard, Data Manipulation, Data Analysis Software, Microsoft Power Platform, Data Import/Export, Data Cleansing

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      Data Science Fundamentals with Python and SQL

      Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Web Scraping, Relational Databases, Stored Procedure, Databases, Computer Programming Tools, Automation, Data Analysis Software, Data Science, Python Programming

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      71K reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      Meta

      Python Data Analytics

      Skills you'll gain: Pandas (Python Package), Data Analysis, Exploratory Data Analysis, Data Modeling, Data Manipulation, Jupyter, Data Processing, Matplotlib, Programming Principles, Data Cleansing, Data Visualization Software, Python Programming, Scripting

      4.3
      Rating, 4.3 out of 5 stars
      ·
      194 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      Learn SQL Basics for Data Science

      Skills you'll gain: Data Governance, Presentations, Data Cleansing, Feature Engineering, SQL, Apache Spark, A/B Testing, Distributed Computing, Descriptive Statistics, Data Lakes, Data Quality, Data Storytelling, Data Analysis, Peer Review, Exploratory Data Analysis, Data Manipulation, Data Pipelines, Databricks, Database Design, Query Languages

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18K reviews

      Beginner · Specialization · 3 - 6 Months

    • M

      Meta

      Data Analysis with Spreadsheets and SQL

      Skills you'll gain: Data Visualization Software, Spreadsheet Software, Correlation Analysis, Google Sheets, Pivot Tables And Charts, Dashboard, Data Analysis, Data Storytelling, Tableau Software, Descriptive Statistics, Data Cleansing, Exploratory Data Analysis, Data Manipulation, Data-Driven Decision-Making, Statistical Analysis, SQL

      4.6
      Rating, 4.6 out of 5 stars
      ·
      221 reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      Introduction to Probability and Data with R

      Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Statistical Software, Descriptive Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    • M

      Microsoft

      Data Analysis and Visualization with Power BI

      Skills you'll gain: Dashboard, Power BI, Data Storytelling, Data Visualization Software, Data Presentation, Advanced Analytics, Statistical Reporting, Interactive Data Visualization, Report Writing, Management Reporting, Business Intelligence, Data Analysis, Web Content Accessibility Guidelines, Key Performance Indicators (KPIs), Time Series Analysis and Forecasting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      754 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Business Analytics

      Skills you'll gain: People Analytics, Data-Driven Decision-Making, Human Capital, Business Analytics, Descriptive Analytics, Business Intelligence, Financial Data, Marketing Analytics, Analytics, Talent Management, Financial Analysis, Predictive Analytics, Human Resources Management and Planning, Peer Review, Business Analysis, Financial Statement Analysis, Financial Forecasting, Customer Insights, Workforce Planning, Demand Planning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Introduction to Data Analysis using Microsoft Excel

      Skills you'll gain: Microsoft Excel, Excel Formulas, Spreadsheet Software, Pivot Tables And Charts, Data Analysis, Data Manipulation, Data Mining

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • M

      Meta

      Meta Database Engineer

      Skills you'll gain: MySQL, Database Design, Version Control, Database Management Systems, Database Management, MySQL Workbench, Extract, Transform, Load, Data Modeling, Data Structures, SQL, Unix Commands, Relational Databases, Databases, Git (Version Control System), Database Systems, Stored Procedure, Object Oriented Programming (OOP), Unit Testing, Algorithms, Django (Web Framework)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    Exploratory Data Analysis learners also search

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

    • Data Engineering Foundations: IBM
    • Data Analysis Using SQL: Fractal Analytics
    • Excel Power Tools for Data Analysis: Macquarie University
    • Data Science Fundamentals with Python and SQL: IBM
    • Python Data Analytics: Meta
    • Learn SQL Basics for Data Science: University of California, Davis
    • Data Analysis with Spreadsheets and SQL: Meta
    • Introduction to Probability and Data with R: Duke University
    • Data Analysis and Visualization with Power BI: Microsoft
    • Business Analytics: University of Pennsylvania

    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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