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    • Exploratory Data Analysis

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    323 results for "exploratory data analysis"

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      IBM Skills Network

      IBM Applied AI

      Skills you'll gain: Machine Learning, Cloud Computing, IBM Cloud, Python Programming, Data Analysis, Computer Vision, Computer Programming, Computer Science, Data Structures, Programming Principles, Algebra, Applied Machine Learning, Computational Thinking, Data Science, Computer Graphics, Theoretical Computer Science, Computer Graphic Techniques, Deep Learning, Natural Language Processing, Statistical Programming, Algorithms, Artificial Neural Networks, Machine Learning Software, Basic Descriptive Statistics, Computational Logic, Design and Product, Exploratory Data Analysis, Human Computer Interaction, Interactive Design, Other Web Frameworks, Product Design, Web Development, Application Development, Cloud API, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Operating Systems, Software Engineering, Software Engineering Tools, Software Testing, Systems Design, Web Development Tools

      4.6

      (42.8k reviews)

      Beginner · Professional Certificate · 3-6 Months

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      DeepLearning.AI

      Machine Learning Engineering for Production (MLOps)

      Skills you'll gain: Machine Learning, Applied Machine Learning, DevOps, Python Programming, Statistical Programming, Tensorflow, Exploratory Data Analysis, Feature Engineering, Probability & Statistics, Cloud Computing, Data Management, Data Warehousing, Extract, Transform, Load, Computer Programming, Computer Vision, Deep Learning, Advertising, Business Analysis, Change Management, Communication, Computer Networking, Data Analysis, Data Visualization, Estimation, General Statistics, Leadership and Management, Machine Learning Algorithms, Marketing, Network Security, Security Engineering, Security Strategy, Statistical Visualization, Strategy and Operations

      4.7

      (2.9k reviews)

      Advanced · Specialization · 3-6 Months

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      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Machine Learning, Business Analysis, Applied Machine Learning, Business Transformation, Data Analysis, Data Model, Deep Learning, Exploratory Data Analysis, Forecasting, Human Computer Interaction, Natural Language Processing, People Analysis, Probability & Statistics, Reinforcement Learning, Statistical Analysis, Artificial Neural Networks, Machine Learning Algorithms

      4.8

      (37.9k reviews)

      Beginner · Course · 1-4 Weeks

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      University of California, Davis

      Learn SQL Basics for Data Science

      Skills you'll gain: SQL, Data Management, Statistical Programming, Apache, Big Data, Databases, Data Analysis, Data Analysis Software, Extract, Transform, Load, Data Warehousing, Machine Learning, Basic Descriptive Statistics, Computer Programming, Data Science, Exploratory Data Analysis, General Statistics, Leadership and Management, Probability & Statistics, Python Programming, Statistical Analysis

      4.6

      (15.5k reviews)

      Beginner · Specialization · 3-6 Months

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      University of Pennsylvania

      Business Analytics

      Skills you'll gain: Business Analysis, Data Analysis, Probability & Statistics, Statistical Analysis, General Statistics, Research and Design, Forecasting, Strategy and Operations, Correlation And Dependence, Financial Analysis, Accounting, Human Resources, Marketing, Operational Analysis, Operations Management, Operations Research, Probability Distribution, Spreadsheet Software, Supply Chain and Logistics, Customer Analysis, Financial Accounting, Market Analysis, Market Research, Basic Descriptive Statistics, Exploratory Data Analysis, Finance, People Management, Performance Management, Regulations and Compliance, Statistical Tests, Talent Management, Collaboration, Communication, Critical Thinking, Data Management, Data Mining, Data Model, Data Visualization, Generally Accepted Accounting Principles (GAAP), HR Tech, Leadership Development, Leadership and Management, MarTech, Marketing Management, Media Strategy & Planning, Microsoft Excel, Organizational Development, Plot (Graphics), Process Analysis, Recruitment, Statistical Programming, Statistical Visualization, Applied Mathematics, Big Data, Business Psychology, Computational Logic, Computer Programming, Computer Programming Tools, Data Analysis Software, Data Structures, Decision Making, Entrepreneurship, Estimation, Mathematics, Network Analysis, People Analysis, People Development, Regression, Sales, Strategy, Theoretical Computer Science

      4.6

      (17.2k reviews)

      Beginner · Specialization · 3-6 Months

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      Johns Hopkins University

      Data Science

      Skills you'll gain: R Programming, Data Analysis, Statistical Programming, Data Science, General Statistics, Statistical Analysis, Probability & Statistics, Statistical Tests, Machine Learning, Exploratory Data Analysis, Basic Descriptive Statistics, Machine Learning Software, Linear Algebra, Bayesian Statistics, Correlation And Dependence, Econometrics, Estimation, Regression, Data Visualization Software, Software Visualization, Statistical Visualization, Probability Distribution, Theoretical Computer Science, Data Visualization, Interactive Data Visualization, Natural Language Processing, Plot (Graphics), Big Data, Computer Programming, Computer Programming Tools, Data Structures, Experiment, Machine Learning Algorithms, Software Engineering Tools, Spreadsheet Software, Algorithms, Application Development, Applied Machine Learning, Business Analysis, Data Management, Extract, Transform, Load, Knitr

      4.5

      (50k reviews)

      Beginner · Specialization · 3-6 Months

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      IBM Skills Network

      IBM Machine Learning

      Skills you'll gain: Machine Learning, Probability & Statistics, General Statistics, Forecasting, Machine Learning Algorithms, Regression, Deep Learning, Data Analysis, Theoretical Computer Science, Artificial Neural Networks, Statistical Machine Learning, Algorithms, Business Analysis, Dimensionality Reduction, Exploratory Data Analysis, Feature Engineering, Computer Vision, Applied Machine Learning, Bayesian Statistics, NoSQL, Probability Distribution, Human Resources, Leadership Development, Leadership and Management, Data Management, Data Structures, Experiment, Linear Algebra, Mathematics, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Visualization, Natural Language Processing, Python Programming, Reinforcement Learning, Statistical Programming, Statistical Visualization, Algebra, Application Development, Basic Descriptive Statistics, Correlation And Dependence, Data Analysis Software, Estimation, SQL, Software Engineering, Statistical Analysis, Statistical Tests

      4.6

      (1.5k reviews)

      Intermediate · Professional Certificate · 3-6 Months

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      Google Cloud

      Preparing for Google Cloud Certification: Machine Learning Engineer

      Skills you'll gain: Machine Learning, Cloud Computing, Google Cloud Platform, Computer Programming, Cloud Platforms, Statistical Programming, Python Programming, Data Management, Applied Machine Learning, Feature Engineering, Tensorflow, Deep Learning, DevOps, Entrepreneurship, Probability & Statistics, Data Analysis, Big Data, Artificial Neural Networks, Business Psychology, Data Visualization, Exploratory Data Analysis, Regression, SQL, Statistical Visualization, Theoretical Computer Science, Data Science, Kubernetes, Apache, Basic Descriptive Statistics, Bayesian Statistics, Computational Thinking, Computer Architecture, Computer Networking, Data Model, Data Structures, Extract, Transform, Load, General Statistics, Hardware Design, Machine Learning Algorithms, Machine Learning Software, Network Security, Performance Management, Security Engineering, Security Strategy, Statistical Machine Learning, Strategy and Operations, Algorithms, Business Analysis, Cloud Applications, Cloud Infrastructure, Cloud Storage, Data Analysis Software, Data Architecture, Data Warehousing, Database Application, Databases, Dimensionality Reduction, Distributed Computing Architecture, Full-Stack Web Development, Information Technology, Natural Language Processing, Statistical Analysis, Web Development

      4.6

      (25.1k reviews)

      Intermediate · Professional Certificate · 3-6 Months

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      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: R Programming, Data Analysis, Data Science, Exploratory Data Analysis, Statistical Programming, Data Visualization Software, Software Visualization, Statistical Visualization, Basic Descriptive Statistics, General Statistics, Big Data, Computer Programming, Computer Programming Tools, Data Structures, Experiment, Linear Algebra, Machine Learning Software, Probability & Statistics, Probability Distribution, Software Engineering Tools, Spreadsheet Software, Statistical Tests, Application Development, Business Analysis, Data Management, Data Visualization, Extract, Transform, Load, Knitr, Plot (Graphics)

      4.6

      (47.3k reviews)

      Beginner · Specialization · 3-6 Months

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      University of Illinois at Urbana-Champaign

      Digital Marketing

      Skills you'll gain: Marketing, Digital Marketing, Research and Design, Communication, Entrepreneurship, Sales, Leadership and Management, Business, Marketing Management, Market Research, Marketing Design, Strategy and Operations, Media Strategy & Planning, Media Production, Design and Product, Strategy, Business Analysis, Market Analysis, Product Marketing, Customer Analysis, Advertising Sales, Business Development, Product Management, Advertising, Brand Management, MarTech, Influencing, Social Media, Business Design, Collaboration, Data Analysis, Finance, Public Relations, Search Engine Optimization, Web Design, Web Development, Business Psychology, Change Management, Customer Support, Human Learning, Journalism, Marketing Psychology, Packaging and Labeling, Product Design, Survey Creation, Visual Design, Accounting, Back-End Web Development, Big Data, Computer Graphics, Data Analysis Software, Data Management, Data Visualization, Exploratory Data Analysis, Human Computer Interaction, Product Development, Statistical Analysis, Supply Chain and Logistics, Virtual Reality

      4.7

      (22k reviews)

      Beginner · Specialization · 3-6 Months

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      IBM Skills Network

      IBM Introduction to Machine Learning

      Skills you'll gain: Machine Learning, Machine Learning Algorithms, Regression, Data Analysis, General Statistics, Probability & Statistics, Theoretical Computer Science, Statistical Machine Learning, Algorithms, Dimensionality Reduction, Business Analysis, Exploratory Data Analysis, Feature Engineering, Bayesian Statistics, NoSQL, Probability Distribution, Human Resources, Leadership Development, Leadership and Management, Applied Machine Learning, Computer Vision, Data Management, Data Structures, Experiment, Linear Algebra, Mathematics, Algebra, Basic Descriptive Statistics, Computer Programming, Correlation And Dependence, Data Analysis Software, Data Visualization, Deep Learning, Estimation, Python Programming, SQL, Statistical Analysis, Statistical Programming, Statistical Tests

      4.6

      (1.4k reviews)

      Intermediate · Specialization · 3-6 Months

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      University of California, Davis

      Data Visualization with Tableau

      Skills you'll gain: Data Visualization, Data Visualization Software, Tableau Software, Data Analysis, Business Analysis, Business Intelligence, Data Analysis Software, Interactive Data Visualization, Statistical Visualization, Software Visualization, Plot (Graphics), Storytelling, Communication, Exploratory Data Analysis, Geovisualization, Persona Research, Research and Design, Statistical Analysis, Visual Design, Probability & Statistics

      4.5

      (7.3k reviews)

      Beginner · Specialization · 3-6 Months

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

    • IBM Applied AI: IBM Skills Network
    • Machine Learning Engineering for Production (MLOps): DeepLearning.AI
    • AI For Everyone: DeepLearning.AI
    • Learn SQL Basics for Data Science: University of California, Davis
    • Business Analytics: University of Pennsylvania
    • Data Science: Johns Hopkins University
    • IBM Machine Learning: IBM Skills Network
    • Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
    • Data Science: Foundations using R: Johns Hopkins University
    • Digital Marketing: University of Illinois at Urbana-Champaign

    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.‎

    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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