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    • Linear Regression

    Linear Regression Courses Online

    Explore linear regression for statistical modeling. Learn to analyze relationships between variables and make predictions based on data.

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    Explore the Linear Regression Course Catalog

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science: Statistics and Machine Learning

      Skills you'll gain: Shiny (R Package), Rmarkdown, Regression Analysis, Leaflet (Software), Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Data Visualization, Statistical Machine Learning, Feature Engineering, Statistical Analysis, Statistical Modeling, Probability, Data Science, Data Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Everyday Excel

      Skills you'll gain: Data Import/Export, Microsoft Excel, Regression Analysis, Data Validation, Data Visualization, Depreciation, Data Management, Excel Macros, Excel Formulas, Statistical Modeling, Financial Analysis, Cash Flows, Predictive Modeling, Financial Modeling, Analysis, Microsoft Word, Business Mathematics, Mathematical Modeling, Complex Problem Solving, Financial Forecasting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Santa Cruz

      Bayesian Statistics

      Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Analysis, Probability, Statistical Machine Learning, Statistical Methods, Statistical Analysis, Advanced Analytics, Mathematical Modeling, Microsoft Excel, Markov Model, Probability Distribution, Probability & Statistics, Unsupervised Learning, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Build Wireframes and Low-Fidelity Prototypes

      Skills you'll gain: Storyboarding, Wireframing, Figma (Design Software), Information Architecture, User Story, User Experience Design, User Centered Design, Prototyping, Usability, User Interface and User Experience (UI/UX) Design, Mockups, User Flows

      4.9
      Rating, 4.9 out of 5 stars
      ·
      9.3K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Unsupervised Learning, Recommenders, Reinforcement Learning

      Skills you'll gain: Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Reinforcement Learning, Statistical Machine Learning, Artificial Neural Networks, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms, Collaborative Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      4.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Mathematics for Machine Learning: Multivariate Calculus

      Skills you'll gain: Regression Analysis, Calculus, Advanced Mathematics, Machine Learning Algorithms, Statistical Analysis, Linear Algebra, Artificial Neural Networks, Python Programming, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Neuroscience and Neuroimaging

      Skills you'll gain: Magnetic Resonance Imaging, Neurology, Medical Imaging, Anatomy, Radiology, Image Analysis, Data Analysis, X-Ray Computed Tomography, Analysis, Data Manipulation, Experimentation, R Programming, Statistical Analysis, Psychology, Network Analysis, Data Processing, Regression Analysis, Research Design, Scientific Visualization, Time Series Analysis and Forecasting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.3K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Business Statistics and Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Analysis, Statistical Modeling, Excel Formulas, Data Analysis, Data Presentation, Statistics, Business Analysis, Statistical Methods, Sample Size Determination, Statistical Inference

      4.7
      Rating, 4.7 out of 5 stars
      ·
      13K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I
      U
      I

      Multiple educators

      Data Science Foundations

      Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Correlation Analysis, Web Scraping, NumPy, Probability & Statistics, Predictive Modeling, Big Data, Automation, Data Visualization Software, Data Collection, Data Science, GitHub, Machine Learning Algorithms, Unsupervised Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      113K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Foundations for Business

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

      4.7
      Rating, 4.7 out of 5 stars
      ·
      94K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      T

      The Hong Kong University of Science and Technology

      Matrix Algebra for Engineers

      Skills you'll gain: Linear Algebra, Engineering Calculations, Algebra, Engineering Analysis, General Mathematics, Advanced Mathematics, Applied Mathematics

      4.9
      Rating, 4.9 out of 5 stars
      ·
      4.5K reviews

      Beginner · Course · 1 - 4 Weeks

    Linear Regression learners also search

    Regression
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    Logistic Regression
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    1…678…74

    In summary, here are 10 of our most popular linear regression courses

    • Data Science: Statistics and Machine Learning: Johns Hopkins University
    • Meta Data Analyst: Meta
    • Everyday Excel: University of Colorado Boulder
    • Bayesian Statistics: University of California, Santa Cruz
    • Build Wireframes and Low-Fidelity Prototypes: Google
    • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
    • Mathematics for Machine Learning: Multivariate Calculus: Imperial College London
    • Neuroscience and Neuroimaging: Johns Hopkins University
    • Business Statistics and Analysis: Rice University
    • Data Science Foundations: IBM

    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 Linear Regression

    Linear regression is a type of statistical data analysis that examines which variables help significantly predict the outcome of a situation. You can use linear regression to determine the relationships between one dependent variable and one or more independent variables to sort out which variables will contribute most to the outcome you seek to achieve. Linear regression also helps you forecast the impact that changes to variables will make in different scenarios. It's a tool you can use to help predict outcomes and make adjustments to help achieve the outcome you're looking for.‎

    If you're in a career that relies on data analysis, linear regression is a tool that can help you determine the relationship between variables that affect scenarios that you need to predict or plan for. You can use linear regression to anticipate how the factors that affect a situation now will make a difference in the future. For example, you can use linear regression to predict the cost of a project or the amount of time it will take to complete the project based on different variables. Linear regression can help you make more informed and educated decisions to better navigate the present and plan for the future.‎

    Data analysts use linear regression in different areas of business to determine which variables affect outcomes the most. You can apply linear regression as a data scientist or analyst with a single company or in a consultant role across multiple businesses. You can even set up your own business as a consultant to be in control of your own schedule and career trajectory. Analysts use linear regression in polling and surveys as well as in policy research fields, and various corporations use data analysis to help plan for the future. You can also apply your knowledge of linear regression in higher education and as a professor or research assistant.‎

    You can use online courses to learn linear regression in order to deepen your knowledge and skills in your current job or to find a new career. Whether you're already familiar with linear regression or whether you're brand new to the concept, online courses can give you the knowledge you need to apply linear regression in your workplace. Online courses not only teach you the concepts, but they also provide you with real-life applications of what you're learning. One of the biggest benefits of online learning is that you can sharpen your skills in a way that fits your schedule and lifestyle. You can walk away from your online learning confident in what you've discovered about linear regression and prepared to apply it to your career.‎

    Online Linear Regression courses offer a convenient and flexible way to enhance your knowledge or learn new Linear Regression skills. Choose from a wide range of Linear Regression courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Linear Regression, 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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