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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

      Duke University

      Behavioral Finance

      Skills you'll gain: Behavioral Economics, Decision Making, Financial Planning, Finance, Consumer Behaviour, Financial Market, Economics, Psychology, Risk Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      P

      Packt

      Master Retrieval-Augmented Generation (RAG) Systems

      Skills you'll gain: Large Language Modeling, Prompt Engineering, Generative AI, Interactive Data Visualization, Text Mining, Data Processing, Unstructured Data, Scalability

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Fundamentals of Data Visualization

      Skills you'll gain: Data Visualization Software, Interactive Data Visualization, Visualization (Computer Graphics), User Centered Design, Statistical Visualization, Data Presentation, Usability, Data Storytelling, Human Computer Interaction, User Research, Usability Testing, Requirements Analysis, Design Elements And Principles

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      36 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Specialized Models: Time Series and Survival Analysis

      Skills you'll gain: Time Series Analysis and Forecasting, Deep Learning, Statistical Analysis, Predictive Modeling, Statistical Methods, Forecasting, Jupyter, Data Cleansing, Applied Machine Learning, Data Transformation, Exploratory Data Analysis, Pandas (Python Package)

      4.5
      Rating, 4.5 out of 5 stars
      ·
      134 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Introduction to Discrete Mathematics for Computer Science

      Skills you'll gain: Graph Theory, Logical Reasoning, Combinatorics, Computational Logic, Deductive Reasoning, Cryptography, Probability, Key Management, Computational Thinking, Encryption, Network Analysis, Public Key Cryptography Standards (PKCS), Algorithms, Theoretical Computer Science, Python Programming, Data Structures, Cybersecurity, Arithmetic, Computer Programming, Mathematical Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      G

      Google

      Design Prompts for Everyday Work Tasks

      Skills you'll gain: Prompt Engineering, Brainstorming, Timelines, Taking Meeting Minutes, Concision, Generative AI, Productivity Software, Business Writing, Artificial Intelligence, Document Management, Project Schedules, Text Mining

      4.9
      Rating, 4.9 out of 5 stars
      ·
      75 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      Regulatory Compliance

      Skills you'll gain: Compliance Training, Compliance Management, General Data Protection Regulation (GDPR), Regulatory Compliance, Law, Regulation, and Compliance, Compliance Reporting, Regulation and Legal Compliance, Legal Risk, Compliance Auditing, Information Privacy, Governance Risk Management and Compliance, Personally Identifiable Information, Regulatory Requirements, Risk Management, Internal Communications, Procedure Development, Data Security, Continuous Monitoring, Business Ethics, Internal Controls

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.6K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      P

      Packt

      Natural Language Processing - Probability Models in Python

      Skills you'll gain: Natural Language Processing, Text Mining, Scikit Learn (Machine Learning Library), Dimensionality Reduction, Statistical Machine Learning, Unsupervised Learning, Python Programming, Bayesian Statistics, NumPy, Supervised Learning, Machine Learning

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      W

      Whizlabs

      Azure ML: Explore & Configure the Machine Learning Workspace

      Skills you'll gain: Statistical Modeling, Microsoft Azure, Data Science, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Statistics, MLOps (Machine Learning Operations), Azure Synapse Analytics, Cloud Computing, Data Management, Virtual Machines

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      S

      Simplilearn

      Introduction Course to Autoencoders, VAEs, and GANs

      Skills you'll gain: Generative AI, Deep Learning, Tensorflow, Image Analysis, Applied Machine Learning, Computer Vision, Artificial Neural Networks, Unsupervised Learning

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      C

      Coursera Instructor Network

      GenAI for Field Sales Agents: Local Market Insights

      Skills you'll gain: Sales Territory Management, Generative AI Agents, Sales Strategy, Customer Engagement, Sales Process, Lead Generation, Sales, Customer experience improvement, Real Time Data, Customer Insights, Market Analysis, Ethical Standards And Conduct, Performance Analysis

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      P

      Packt

      Harnessing LLMs & Text-Embeddings API with Google Vertex AI

      Skills you'll gain: Large Language Modeling, Google Cloud Platform, Cloud API, Generative AI, Prompt Engineering, Application Programming Interface (API), Data Visualization, Unsupervised Learning, Natural Language Processing, Applied Machine Learning, Scalability

      Intermediate · Course · 1 - 3 Months

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

    • Behavioral Finance: Duke University
    • Master Retrieval-Augmented Generation (RAG) Systems: Packt
    • Fundamentals of Data Visualization: University of Colorado Boulder
    • Specialized Models: Time Series and Survival Analysis: IBM
    • Introduction to Discrete Mathematics for Computer Science: University of California San Diego
    • Design Prompts for Everyday Work Tasks: Google
    • Regulatory Compliance: University of Pennsylvania
    • Natural Language Processing - Probability Models in Python: Packt
    • Azure ML: Explore & Configure the Machine Learning Workspace: Whizlabs
    • Introduction Course to Autoencoders, VAEs, and GANs: Simplilearn

    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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