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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

    • M

      Macquarie University

      Excel Skills for Business: Intermediate II

      Skills you'll gain: Excel Formulas, Microsoft Excel, Excel Macros, Data Validation, Spreadsheet Software, Data Analysis Expressions (DAX), Data Modeling, Financial Forecasting, Predictive Modeling, Financial Modeling, Workflow Management, Data Integrity, Business Modeling, Automation, Process Optimization

      4.8
      Rating, 4.8 out of 5 stars
      ·
      8.3K reviews

      Intermediate · Course · 1 - 3 Months

    • M

      Macquarie University

      Influencing: Storytelling, Change Management and Governance

      Skills you'll gain: Overcoming Objections, Influencing, Risk Management Framework, Persuasive Communication, Governance, Storytelling, Risk Management, Change Management, Organizational Change, Rapport Building, Meeting Facilitation, Conflict Management, Enterprise Risk Management (ERM), Business Transformation, Risk Analysis, Negotiation, Intercultural Competence, Stakeholder Management, Leadership, Process Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Pennsylvania

      Introduction to Spreadsheets and Models

      Skills you'll gain: Regression Analysis, Spreadsheet Software, Google Sheets, Financial Modeling, Microsoft Excel, Data Modeling, Forecasting, Risk Analysis, Probability & Statistics, Business Modeling, Statistical Analysis, Simulation and Simulation Software, Process Improvement and Optimization

      4.2
      Rating, 4.2 out of 5 stars
      ·
      3.8K reviews

      Mixed · Course · 1 - 4 Weeks

    • G

      Google Cloud

      BigQuery for Data Analysts

      Skills you'll gain: Looker (Software), Big Data, SQL, Data Pipelines, Data Transformation, Extract, Transform, Load, Data Warehousing, Data Cleansing, Data Analysis, Data Visualization Software, Google Sheets, Google Cloud Platform, Data Import/Export, Data Integrity

      4.5
      Rating, 4.5 out of 5 stars
      ·
      57 reviews

      Intermediate · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Data Science in Real Life

      Skills you'll gain: Data Quality, Data Management, Technical Communication, Data Analysis, Data-Driven Decision-Making, Statistical Analysis, Data Science, Statistical Machine Learning, Statistical Inference, A/B Testing, Statistical Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      2.4K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Toronto

      Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Control Systems, Embedded Software, Automation, Deep Learning, Software Architecture, Simulations, Safety Assurance, Artificial Neural Networks, Global Positioning Systems, Hardware Architecture, Systems Architecture, Artificial Intelligence, Estimation, Algorithms, Machine Learning Methods, Predictive Modeling, Scenario Testing, Spatial Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      University of Maryland, College Park

      Cybersecurity for Everyone

      Skills you'll gain: Cyber Risk, Cyber Security Policies, Security Management, Cybersecurity, Risk Management, Cyber Security Strategy, Cyber Attacks, Cyber Governance, Infrastructure Security, Telecommunications, Computer Security Awareness Training, Threat Detection, Enterprise Security, Security Awareness, General Networking, Data Security, Vulnerability, Public Safety and National Security, Governance, Political Sciences

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.9K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Virginia

      Digital Product Management: Modern Fundamentals

      Skills you'll gain: New Product Development, Product Management, Innovation, Product Improvement, Customer Insights, Design and Product, Product Roadmaps, Stakeholder Communications, Customer Engagement, Agile Methodology, Data-Driven Decision-Making, Marketing Analytics, Stakeholder Management, Product Testing, Business Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.3K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Virginia

      Foundations of Business Strategy

      Skills you'll gain: Business Strategy, Strategic Thinking, Competitive Analysis, Organizational Strategy, Strategic Decision-Making, Market Analysis, Analysis, Business Economics, Value Propositions

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Pennsylvania

      Business Analytics Capstone

      Skills you'll gain: Data-Driven Decision-Making, Business Analytics, Business Intelligence, Analytics, Peer Review, Business Analysis, Performance Measurement, Marketing Analytics, Data Strategy, Business Solutions, Business Planning, Business Strategy, Strategic Thinking, Business Strategies, Key Performance Indicators (KPIs), Marketing Effectiveness, Digital Advertising, Advertising

      4.5
      Rating, 4.5 out of 5 stars
      ·
      767 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      Y

      Yale University

      Moral Foundations of Politics

      Skills you'll gain: Political Sciences, Policy Analysis, Social Justice, Social Sciences, European History, Law, Regulation, and Compliance, Governance, Ethical Standards And Conduct, Socioeconomics, Economics

      4.9
      Rating, 4.9 out of 5 stars
      ·
      6K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Minnesota

      Software Development Lifecycle

      Skills you'll gain: User Story, Agile Software Development, Software Design Patterns, Design Thinking, Software Development Methodologies, Software Design, Agile Methodology, Agile Project Management, Engineering Software, Process Mapping, Software Engineering, Kanban Principles, Software Development Life Cycle, Software Quality Assurance, Program Development, Application Security, Scrum (Software Development), Requirements Analysis, Lean Methodologies, Lean Manufacturing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9.6K reviews

      Intermediate · Specialization · 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

    • Excel Skills for Business: Intermediate II: Macquarie University
    • Influencing: Storytelling, Change Management and Governance: Macquarie University
    • Introduction to Spreadsheets and Models: University of Pennsylvania
    • BigQuery for Data Analysts: Google Cloud
    • Data Science in Real Life: Johns Hopkins University
    • Self-Driving Cars: University of Toronto
    • Cybersecurity for Everyone: University of Maryland, College Park
    • Digital Product Management: Modern Fundamentals: University of Virginia
    • Foundations of Business Strategy: University of Virginia
    • Business Analytics Capstone: 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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