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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 Virginia

      Marketing Analytics

      Skills you'll gain: Marketing Analytics, Marketing Effectiveness, Marketing, Marketing Strategies, Regression Analysis, Data-Driven Decision-Making, Strategic Marketing, Brand Management, Resource Allocation, Customer Insights, Predictive Analytics, Advertising Campaigns, Statistical Analysis, A/B Testing, Consumer Behaviour, Return On Investment

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.4K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      SQL Problem Solving

      Skills you'll gain: Data Cleansing, Feature Engineering, A/B Testing, Data Quality, SQL, Data Manipulation, Data Integrity, Time Series Analysis and Forecasting, Data Analysis, Predictive Analytics, Business Metrics

      3.3
      Rating, 3.3 out of 5 stars
      ·
      995 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      Universitat Autònoma de Barcelona

      Competencias digitales. Herramientas de ofimática (Microsoft Word, Excel, Power Point)

      Skills you'll gain: Spreadsheet Software, Data Entry, Document Management, File Management, Data Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.4K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Fundamentals of Quantitative Modeling

      Skills you'll gain: Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Financial Modeling, Business Mathematics, Markov Model, Probability, Predictive Analytics, Process Optimization, Risk Management, Statistics, Probability Distribution, Simulation and Simulation Software, Forecasting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Virginia

      Digital Product Management

      Skills you'll gain: Usability Testing, Agile Product Development, New Product Development, Continuous Delivery, Agile Software Development, User Story, Product Management, Agile Methodology, Product Testing, Agile Project Management, Team Performance Management, Team Management, Design Thinking, Team Building, Team Leadership, Product Improvement, Customer Analysis, Innovation, Analytics, Business Analytics

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

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Accelerated Computer Science Fundamentals

      Skills you'll gain: C++ (Programming Language), Data Structures, Object Oriented Programming (OOP), Object Oriented Design, Graph Theory, Development Environment, Engineering Software, Computer Programming, Software Engineering, Algorithms, Debugging, Program Development, Database Systems, Database Theory, Network Routing, Theoretical Computer Science, Data Storage

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

      Intermediate · Specialization · 1 - 3 Months

    • Status: New
      New
      U

      University of Colorado Boulder

      Statistics and Applied Data Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Statistical Analysis, Regression Analysis, Statistical Programming, Probability, Probability Distribution, Sampling (Statistics), Box Plots, Histogram, R Programming, Statistical Methods, Scatter Plots, Microsoft Excel, Probability & Statistics, Statistics, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      32 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New
      Status: Free
      Free
      M

      Maven Analytics

      ChatGPT & Generative AI for Data Analytics

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, Data Analysis Expressions (DAX), Power BI, Deep Learning, Excel Formulas, Analytics, Google Sheets, Machine Learning Methods, Large Language Modeling, Microsoft Excel, Artificial Intelligence, Python Programming, SQL, Debugging

      4.8
      Rating, 4.8 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Introduction to Marketing

      Skills you'll gain: Go To Market Strategy, Branding, Consumer Behaviour, Strategic Marketing, Marketing, Brand Strategy, Communication Strategies, Marketing Strategy and Techniques, Marketing Communications, Brand Loyalty, Customer experience strategy (CX), Customer Insights, Brand Awareness, Price Negotiation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      13K reviews

      Mixed · Course · 1 - 3 Months

    • G

      Google

      Connect and Protect: Networks and Network Security

      Skills you'll gain: Network Security, Hardening, Network Protocols, Cloud Security, Network Architecture, Intrusion Detection and Prevention, TCP/IP, Vulnerability Assessments, Computer Networking, Cyber Attacks, Network Infrastructure, Firewall, Cloud Computing, Virtual Private Networks (VPN)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Colorado Boulder

      Advanced Business Analytics

      Skills you'll gain: Data Storytelling, Data Presentation, Data Governance, Data Visualization, Predictive Analytics, Analytics, Business Analytics, Data Storage, Data Management, Big Data, Risk Analysis, Databases, Data Modeling, Business Analysis, Business Intelligence, Data Visualization Software, Data Analysis, Decision Making, Data Cleansing, Predictive Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • S

      Snowflake

      Intro to Snowflake for Devs, Data Scientists, Data Engineers

      Skills you'll gain: Data Manipulation, Data Lakes, Data Warehousing, SQL, Data Pipelines, Cloud Applications, Extract, Transform, Load, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Role-Based Access Control (RBAC), Stored Procedure, Generative AI, Large Language Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      79 reviews

      Beginner · Course · 1 - 4 Weeks

    Exploratory Data Analysis learners also search

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

    • Marketing Analytics: University of Virginia
    • SQL Problem Solving: University of California, Davis
    • Competencias digitales. Herramientas de ofimática (Microsoft Word, Excel, Power Point): Universitat Autònoma de Barcelona
    • Fundamentals of Quantitative Modeling: University of Pennsylvania
    • Digital Product Management: University of Virginia
    • Accelerated Computer Science Fundamentals: University of Illinois Urbana-Champaign
    • Statistics and Applied Data Analysis: University of Colorado Boulder
    • ChatGPT & Generative AI for Data Analytics: Maven Analytics
    • Introduction to Marketing: University of Pennsylvania
    • Connect and Protect: Networks and Network Security: Google

    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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