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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

      IBM Business Analyst

      Skills you'll gain: Data Storytelling, Requirements Elicitation, Risk Mitigation, Business Analysis, Business Process Modeling, Risk Analysis, Process Mapping, Process Optimization, Requirements Management, Risk Management, Business Requirements, Stakeholder Management, Work Breakdown Structure, Scope Management, Process Analysis, Stakeholder Engagement, Data Visualization Software, Excel Formulas, Microsoft Excel, Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: AI skills
      AI skills
      G

      Google Cloud

      Google Cloud Data Analytics

      Skills you'll gain: Data Storytelling, Data Governance, Data Presentation, Data Management, Data Pipelines, Data Visualization Software, Dashboard, Data Lakes, Data Architecture, Cloud Infrastructure, Generative AI, Data Infrastructure, Data Cleansing, Data Transformation, Cloud Computing, Data Access, Data Storage Technologies, Data Ethics, Data Analysis, Analytics

      4.4
      Rating, 4.4 out of 5 stars
      ·
      163 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      What is Data Science?

      Skills you'll gain: Data Literacy, Data Mining, Big Data, Cloud Computing, Data Analysis, Data Science, Digital Transformation, Data-Driven Decision-Making, Deep Learning, Machine Learning, Artificial Intelligence

      4.7
      Rating, 4.7 out of 5 stars
      ·
      75K reviews

      Beginner · Course · 1 - 4 Weeks

    • V

      Vanderbilt University

      ChatGPT Advanced Data Analysis

      Skills you'll gain: Prompt Engineering, Data Presentation, ChatGPT, Document Management, Artificial Intelligence, Microsoft Excel, Problem Solving, Data Analysis, Generative AI, Information Management, File Management, Creativity, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      765 reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud Data Engineer

      Skills you'll gain: Data Pipelines, Dataflow, Google Cloud Platform, Real Time Data, Data Maintenance, Data Lakes, Data Storage, MLOps (Machine Learning Operations), Data Analysis, Dashboard, Data Warehousing, Data Processing, Extract, Transform, Load, Cloud Engineering, Data Infrastructure, Cloud Infrastructure, Cloud Storage, Big Data, Tensorflow, Unstructured Data

      4.6
      Rating, 4.6 out of 5 stars
      ·
      19K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • U

      University of California San Diego

      Data Structures and Algorithms

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Network Routing, Program Development, Debugging, Network Model, Bioinformatics, Operations Research, Data Storage, Development Testing, Test Engineering, Software Testing, Theoretical Computer Science, Computational Thinking, Network Analysis, Test Case, Programming Principles, Computer Programming, Epidemiology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      17K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Engineering

      Skills you'll gain: NoSQL, Data Warehousing, Apache Hadoop, SQL, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, IBM Cognos Analytics, MySQL, Apache Spark, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Data Store, Jupyter, Generative AI, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • P

      PwC

      Data Analysis and Presentation Skills: the PwC Approach

      Skills you'll gain: Analytics, Business Analytics, Data Analysis, Microsoft PowerPoint, Data Presentation, Presentations, Excel Formulas, Data-Driven Decision-Making, Dashboard, Data Storytelling, Business Intelligence, Microsoft Excel, Customer Analysis, Data Visualization, Data Visualization Software, Data Literacy, Big Data, Verbal Communication Skills, Data Cleansing, Spreadsheet Software

      4.6
      Rating, 4.6 out of 5 stars
      ·
      11K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Data Analytics with Excel and R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Relational Databases, Big Data, Data Visualization Software, Ggplot2, Database Design, Data Analysis, IBM Cognos Analytics, Statistical Analysis, Data Presentation, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM Data Management

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Data Governance, Data Security, Data Migration, Database Design, Data Literacy, Descriptive Statistics, Extract, Transform, Load, Data Mining, Cloud Storage, Data Visualization Software, Data Store, IBM DB2, Data Management, Relational Databases, MySQL, Excel Formulas

      4.7
      Rating, 4.7 out of 5 stars
      ·
      17K 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

    • IBM Business Analyst: IBM
    • Google Cloud Data Analytics: Google Cloud
    • What is Data Science? : IBM
    • ChatGPT Advanced Data Analysis: Vanderbilt University
    • Preparing for Google Cloud Certification: Cloud Data Engineer: Google Cloud
    • Data Structures and Algorithms: University of California San Diego
    • Data Analysis with R: Duke University
    • IBM Data Engineering: IBM
    • Data Analysis and Presentation Skills: the PwC Approach: PwC
    • IBM Data Analytics with Excel and R: 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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