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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: New
      New
      G

      Google Cloud

      Boost Productivity with Gemini in BigQuery - 简体中文

      Skills you'll gain: Data Pipelines, Exploratory Data Analysis, Google Cloud Platform, Data Cleansing, Interactive Data Visualization, Data Transformation, Data Analysis, Generative AI, SQL

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Privacy & Safety - Français

      Skills you'll gain: Information Privacy, Cloud Security, Generative AI, Personally Identifiable Information, Google Cloud Platform, Data Security, Artificial Intelligence, Safety and Security, Encryption, Machine Learning

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      A

      Amazon Web Services

      Getting Started with Amazon DocumentDB (with MongoDB compatibility)

      Skills you'll gain: Amazon Web Services, MongoDB, NoSQL, Cloud-Based Integration, Cloud Applications, Operational Databases

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      P

      Packt

      Authentic Node.js WebSocket Server Workshop

      Skills you'll gain: Node.JS, Web Servers, Server Side, Full-Stack Web Development, Network Protocols, Javascript, Cryptography, Real Time Data, Debugging, Data Validation

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Responsible AI for Developers: Privacy & Safety - Indonesian

      Skills you'll gain: Generative AI, Information Privacy, Google Cloud Platform, Cloud Security, Application Security, Personally Identifiable Information, Data Ethics, Data Security, Artificial Intelligence, Safety and Security, Data Encryption Standard, Prompt Engineering

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      P

      Packt

      Advanced Docker - Data Persistence and Orchestration

      Skills you'll gain: Docker (Software), Application Deployment, Containerization, Nginx, Microservices, Data Storage, YAML, Command-Line Interface, General Networking

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      G

      Google Cloud

      Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Français

      Skills you'll gain: MLOps (Machine Learning Operations), Generative AI, Continuous Monitoring, Predictive Modeling, Data Ethics, Data Validation, Applied Machine Learning, Google Cloud Platform, Machine Learning

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      P

      Packt

      CertNexus Certified IoT Practitioner (ITP-110)

      Skills you'll gain: Internet Of Things, Software Development Life Cycle, Systems Development, Information Systems Security, General Networking, Cloud Computing, Emerging Technologies, Safety and Security, Automation, Prototyping, Requirements Analysis, Project Planning

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      G

      Google Cloud

      Boost Productivity with Gemini in BigQuery - 한국어

      Skills you'll gain: Exploratory Data Analysis, Prompt Engineering, Generative AI, Data Visualization Software, Google Cloud Platform, Data Cleansing, Data Transformation, Debugging, Natural Language Processing

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Fairness & Bias - 繁體中文

      Skills you'll gain: Data Ethics, Artificial Intelligence, Google Cloud Platform, Open Source Technology, Data Quality, Data Validation, Machine Learning

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      G

      Google Cloud

      Networking in Google Cloud: Fundamentals - 日本語版

      Skills you'll gain: Network Monitoring, Google Cloud Platform, Virtual Private Networks (VPN), Network Troubleshooting, Cloud Infrastructure, Computer Networking, Network Infrastructure, Network Performance Management, Virtual Machines, Network Analysis, Load Balancing

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      G

      Google Cloud

      Boost Productivity with Gemini in BigQuery - Français

      Skills you'll gain: Data Processing, Data Manipulation, Exploratory Data Analysis, Data Cleansing, Big Data, Data Transformation, Google Cloud Platform, Interactive Data Visualization, Generative AI, Debugging, Query Languages, SQL

      Beginner · Course · 1 - 4 Weeks

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

    • Boost Productivity with Gemini in BigQuery - 简体中文: Google Cloud
    • Responsible AI for Developers: Privacy & Safety - Français: Google Cloud
    • Getting Started with Amazon DocumentDB (with MongoDB compatibility): Amazon Web Services
    • Authentic Node.js WebSocket Server Workshop: Packt
    • Responsible AI for Developers: Privacy & Safety - Indonesian: Google Cloud
    • Advanced Docker - Data Persistence and Orchestration: Packt
    • Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Français: Google Cloud
    • CertNexus Certified IoT Practitioner (ITP-110): Packt
    • Boost Productivity with Gemini in BigQuery - 한국어: Google Cloud
    • Responsible AI for Developers: Fairness & Bias - 繁體中文: Google Cloud

    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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