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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

      Deep Learning

      Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Tensorflow, Supervised Learning, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Debugging, Performance Tuning, Keras (Neural Network Library), Python Programming, Machine Learning Algorithms, Analysis, Data Processing

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      146K reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      R Programming

      Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Computer Programming Tools, Program Development, Data Structures, Performance Tuning, Data Import/Export

      4.5
      Rating, 4.5 out of 5 stars
      ·
      22K reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      IBM AI Developer

      Skills you'll gain: Generative AI, Prompt Engineering, Large Language Modeling, Software Development Life Cycle, Unit Testing, ChatGPT, HTML and CSS, Development Environment, Web Design and Development, Jupyter, Hypertext Markup Language (HTML), Software Engineering, Artificial Intelligence, Cascading Style Sheets (CSS), Software Development Tools, Web Development, Application Deployment, Automation, Interviewing Skills, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      68K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      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
      ·
      57K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • C

      Coursera Project Network

      Python for Data Analysis: Pandas & NumPy

      Skills you'll gain: Pandas (Python Package), NumPy, Data Analysis, Data Science, Python Programming, Data Structures, Data Manipulation, Computer Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      333 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • I

      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Feature Engineering, Jupyter, Advanced Mathematics, Data Science, Statistics, Machine Learning Algorithms, Machine Learning Methods, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming, Machine Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google

      Ask Questions to Make Data-Driven Decisions

      Skills you'll gain: Spreadsheet Software, Stakeholder Communications, Dashboard, Data-Driven Decision-Making, Data Analysis, Analytical Skills, Data Presentation, Business Analysis, Expectation Management, Quantitative Research, Communication

      4.7
      Rating, 4.7 out of 5 stars
      ·
      34K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Key Technologies for Business

      Skills you'll gain: Cloud Computing Architecture, Cloud Services, Large Language Modeling, Cloud Security, Data Literacy, Cloud Infrastructure, Data Mining, Cloud Platforms, Cloud Computing, Artificial Intelligence, Generative AI, Data Ethics, Cloud Storage, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure As A Service (IaaS), Big Data, Emerging Technologies, Applied Machine Learning, Data Analysis, Data Science

      4.7
      Rating, 4.7 out of 5 stars
      ·
      100K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      T

      The State University of New York

      Practical Time Series Analysis

      Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Statistical Analysis, Data Analysis, Data Visualization, Mathematical Modeling, Statistical Modeling, Predictive Modeling, Correlation Analysis, Regression Analysis, Descriptive Statistics, Statistical Inference, Software Installation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.7K reviews

      Intermediate · 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
      ·
      47K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      IBM AI Foundations for Business

      Skills you'll gain: Large Language Modeling, Data Literacy, Data Mining, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Information Architecture, Strategic Decision-Making, Enterprise Architecture, Cloud Computing, Applied Machine Learning, Data Analysis, Data Science, Deep Learning, Digital Transformation, Data Strategy, Business Strategy, Business Process Automation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      93K reviews

      Beginner · Specialization · 1 - 3 Months

    • D

      DeepLearning.AI

      Mathematics for Machine Learning and Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Python Programming, Jupyter, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.7K reviews

      Intermediate · Specialization · 1 - 3 Months

    Exploratory Data Analysis learners also search

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    R
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    1…101112…807

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

    • Deep Learning: DeepLearning.AI
    • R Programming: Johns Hopkins University
    • IBM AI Developer: IBM
    • IBM Relational Database Administrator: IBM
    • Python for Data Analysis: Pandas & NumPy: Coursera Project Network
    • Mathematics for Machine Learning: Imperial College London
    • Ask Questions to Make Data-Driven Decisions: Google
    • Key Technologies for Business: IBM
    • Practical Time Series Analysis: The State University of New York
    • AI For Everyone: DeepLearning.AI

    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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