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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

    • D

      DeepLearning.AI

      Structuring Machine Learning Projects

      Skills you'll gain: Deep Learning, Applied Machine Learning, Machine Learning, Tensorflow, PyTorch (Machine Learning Library), Debugging, Artificial Intelligence, Keras (Neural Network Library), Data Quality, Performance Tuning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      50K reviews

      Beginner · Course · 1 - 4 Weeks

    • G

      Google

      The Power of Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Data Analysis, Statistical Analysis, Probability Distribution, Statistical Methods, Advanced Analytics, Analytics, Statistics, Data Literacy, Statistical Inference, Probability, Statistical Software, Statistical Programming, A/B Testing, Sample Size Determination, Jupyter, Technical Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      779 reviews

      Advanced · Course · 1 - 3 Months

    • G

      Google

      Crash Course on Python

      Skills you'll gain: Programming Principles, Scripting, Python Programming, Computer Programming, Computational Thinking, Algorithms, Data Structures, Integrated Development Environments, Debugging, Development Environment

      4.8
      Rating, 4.8 out of 5 stars
      ·
      39K reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google

      Get Started with Python

      Skills you'll gain: Object Oriented Programming (OOP), Data Analysis, Data Structures, Jupyter, Python Programming, NumPy, Pandas (Python Package), Programming Principles, Scripting, Data Manipulation, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.5K reviews

      Advanced · Course · 1 - 3 Months

    • Status: New
      New
      V

      Vanderbilt University

      Generative AI SQL Database Specialist with ChatGPT

      Skills you'll gain: Prompt Engineering, ChatGPT, Database Design, Productivity, Data Migration, Generative AI, Software Documentation, SQL, Dashboard, Artificial Intelligence, Database Management, Data Visualization, Large Language Modeling, Gap Analysis, Database Architecture and Administration, Technical Design, Data Storytelling, Data Analysis, Debugging, Data-Driven Decision-Making

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.7K reviews

      Intermediate · Specialization · 1 - 3 Months

    • U

      University of Pennsylvania

      Introduction to Finance and Accounting

      Skills you'll gain: Financial Statements, Return On Investment, Financial Statement Analysis, Financial Reporting, Capital Budgeting, Financial Accounting, Financial Modeling, Working Capital, Balance Sheet, Accrual Accounting, Cash Flows, Income Statement, Finance, Accounting, Financial Analysis, Tax Planning, Equities, Financial Planning, Business Valuation, Corporate Finance

      4.6
      Rating, 4.6 out of 5 stars
      ·
      14K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Security in Google Cloud

      Skills you'll gain: Google Cloud Platform, Cloud Infrastructure, Identity and Access Management, Data Loss Prevention, Distributed Denial-Of-Service (DDoS) Attacks, Prompt Engineering, Kubernetes, Cloud Security, Containerization, OAuth, Cloud Storage, Cloud Services, Application Deployment, Virtual Machines, Security Controls, Cloud Computing, Application Development, Data Storage Technologies, Threat Management, Virtual Private Networks (VPN)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      49K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Data Warehouse Fundamentals

      Skills you'll gain: Data Warehousing, Extract, Transform, Load, Star Schema, IBM DB2, Data Modeling, Snowflake Schema, PostgreSQL, Database Design, Data Architecture, Data Mart, Database Systems, Data Lakes, Data Validation, Data Integration, SQL, Data Cleansing, Query Languages, Data Quality

      4.5
      Rating, 4.5 out of 5 stars
      ·
      227 reviews

      Intermediate · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Python for Genomic Data Science

      Skills you'll gain: Bioinformatics, Data Structures, Jupyter, Python Programming, Programming Principles, Scripting Languages, Scripting, Data Processing, Computer Programming, Data Manipulation, File Management

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Introduction to Generative AI Learning Path

      Skills you'll gain: Large Language Modeling, Generative AI, Prompt Engineering, Data Ethics, Google Cloud Platform, Business Ethics, Application Development, Artificial Intelligence, Accountability, Regulatory Compliance, Compliance Training, Ethical Standards And Conduct, Data Governance, Artificial Intelligence and Machine Learning (AI/ML), Governance, Organizational Effectiveness, Machine Learning, Machine Learning Methods, Decision Making

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.9K reviews

      Intermediate · Specialization · 1 - 3 Months

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud DevOps Engineer

      Skills you'll gain: Site Reliability Engineering, Kubernetes, Application Performance Management, Google Cloud Platform, Cloud Infrastructure, System Monitoring, Prompt Engineering, Application Deployment, Identity and Access Management, DevOps, CI/CD, Containerization, Cloud Storage, Cloud Security, Cloud Services, Cloud Management, Service Level Agreement, Safety Culture, Event Monitoring, Culture Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      54K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Generative AI for Business Intelligence (BI) Analysts

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI, Interactive Data Visualization, Business Intelligence, Data Presentation, Infographics, OpenAI, Dashboard, Data Storytelling, Large Language Modeling, Artificial Intelligence, Program Development, SQL, Data Analysis, Image Analysis, Content Creation, Business Ethics, Virtual Environment, Natural Language Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.3K reviews

      Intermediate · Specialization · 1 - 3 Months

    Exploratory Data Analysis learners also search

    Data Analysis
    Analysis
    R
    Data
    Beginner Data Analysis
    Beginner Data Analysis
    Data Analysis Projects
    Data Science
    1…181920…807

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

    • Structuring Machine Learning Projects: DeepLearning.AI
    • The Power of Statistics: Google
    • Crash Course on Python: Google
    • Get Started with Python: Google
    • Generative AI SQL Database Specialist with ChatGPT: Vanderbilt University
    • Introduction to Finance and Accounting: University of Pennsylvania
    • Security in Google Cloud: Google Cloud
    • Data Warehouse Fundamentals: IBM
    • Python for Genomic Data Science: Johns Hopkins University
    • Introduction to Generative AI Learning Path: 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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