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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

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Developer

      Skills you'll gain: Prompt Engineering, HTML and CSS, Software Development Life Cycle, Software Architecture, Large Language Modeling, Flask (Web Framework), Generative AI, Software Design, Unit Testing, ChatGPT, Jupyter, Artificial Intelligence, Scrum (Software Development), Software Engineering, OpenAI, Agile Methodology, Bootstrap (Front-End Framework), Python Programming, Interviewing Skills, Professional Development

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      70K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Key Technologies for Business

      Skills you'll gain: Cloud Computing Architecture, Cloud Services, Large Language Modeling, Cloud Security, Cloud Technologies, Data Literacy, Cloud Infrastructure, Data Mining, Artificial Intelligence, Cloud Platforms, Cloud Hosting, Cloud Engineering, OpenAI, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Cloud Computing, Data Analysis, Data Science

      4.7
      Rating, 4.7 out of 5 stars
      ·
      101K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Using Python to Access Web Data

      Skills you'll gain: Web Scraping, JSON, Network Protocols, Web Services, Restful API, Application Programming Interface (API), Extensible Markup Language (XML), Data Import/Export, Data Access, TCP/IP, Python Programming, Scripting, Hypertext Markup Language (HTML), Data Capture, Text Mining

      4.8
      Rating, 4.8 out of 5 stars
      ·
      44K reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Data Ethics, Market Opportunities, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Team Building, Machine Learning, Strategic Thinking, Data Science, Needs Assessment, Deep Learning, Business Ethics, Artificial Neural Networks, Engineering Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      48K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      P

      PwC

      Data Visualization with Advanced Excel

      Skills you'll gain: Data Presentation, Dashboard, Data Storytelling, Data Visualization Software, Microsoft Excel, Spreadsheet Software, Excel Formulas, Graphing, Pivot Tables And Charts, Data Modeling, Databases, Data Analysis, Simulation and Simulation Software

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Visualization and Dashboards with Excel and Cognos

      Skills you'll gain: Data Storytelling, Data Visualization Software, Dashboard, IBM Cognos Analytics, Tree Maps, Scatter Plots, Pivot Tables And Charts, Microsoft Excel, Histogram

      4.7
      Rating, 4.7 out of 5 stars
      ·
      4.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Illinois Urbana-Champaign

      Data Visualization

      Skills you'll gain: Data Visualization Software, Data Presentation, Interactive Data Visualization, Data Storytelling, Dashboard, Tableau Software, Plot (Graphics), Scatter Plots, Data Mapping, Graphing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.4K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Sequences, Time Series and Prediction

      Skills you'll gain: Tensorflow, Time Series Analysis and Forecasting, Applied Machine Learning, Deep Learning, Predictive Modeling, Artificial Neural Networks, Forecasting, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.1K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      I

      IBM

      IBM Relational Database Administrator

      Skills you'll gain: Data Warehousing, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, SQL, Database Administration, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Transformation, Data Store, IBM DB2, Jupyter, Generative AI

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

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      M

      Macquarie University

      Excel Skills for Statistics and Data Analysis: Intermediate

      Skills you'll gain: Interactive Data Visualization, Pivot Tables And Charts, Statistical Inference, Microsoft Excel, Correlation Analysis, Statistics, Statistical Hypothesis Testing, Probability & Statistics, Statistical Analysis, Regression Analysis, Data Analysis, Sampling (Statistics), Descriptive Statistics, Forecasting

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Business and Financial Modeling

      Skills you'll gain: Risk Modeling, Financial Statements, Probability Distribution, Mathematical Modeling, Statistical Modeling, Portfolio Management, Regression Analysis, Business Modeling, Financial Modeling, Strategic Decision-Making, Risk Management, Presentations, Decision Making, Data Visualization, Microsoft PowerPoint, Predictive Modeling, Investment Management, Data Modeling, Spreadsheet Software, Google Sheets

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Azure Data Fundamentals DP-900 Exam Prep

      Skills you'll gain: Azure Synapse Analytics, Microsoft Azure, Power BI, Databricks, Data Processing, Cloud Services, Data Warehousing, Database Systems, Databases, Dashboard, Data Architecture, NoSQL, Apache Spark, Database Administration, Relational Databases, MySQL, Data Store, SQL, Cloud Storage, Database Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      829 reviews

      Beginner · 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

    • IBM AI Developer: IBM
    • Key Technologies for Business: IBM
    • Using Python to Access Web Data: University of Michigan
    • AI For Everyone: DeepLearning.AI
    • Data Visualization with Advanced Excel: PwC
    • Data Visualization and Dashboards with Excel and Cognos: IBM
    • Data Visualization: University of Illinois Urbana-Champaign
    • Sequences, Time Series and Prediction: DeepLearning.AI
    • IBM Relational Database Administrator: IBM
    • Excel Skills for Statistics and Data Analysis: Intermediate: Macquarie University

    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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