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    • Logistic Regression

    Logistic Regression Courses Online

    Study logistic regression for binary classification. Learn to model and predict binary outcomes using logistic regression techniques.

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    Explore the Logistic Regression Course Catalog

    • U

      University of Washington

      Machine Learning

      Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Intermediate · Specialization · 3 - 6 Months

    • 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

    • 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

    • 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

    • U

      University of Pennsylvania

      Introduction to Spreadsheets and Models

      Skills you'll gain: Regression Analysis, Spreadsheet Software, Google Sheets, Financial Modeling, Microsoft Excel, Data Modeling, Forecasting, Risk Analysis, Probability & Statistics, Business Modeling, Statistical Analysis, Simulation and Simulation Software, Process Improvement and Optimization

      4.2
      Rating, 4.2 out of 5 stars
      ·
      3.8K reviews

      Mixed · Course · 1 - 4 Weeks

    • 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

    • J

      Johns Hopkins University

      Advanced Linear Models for Data Science 1: Least Squares

      Skills you'll gain: Regression Analysis, Statistical Modeling, R Programming, Linear Algebra, Data Science, Mathematical Modeling, Predictive Modeling, Statistical Analysis, Applied Mathematics, Advanced Mathematics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      187 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free
      Free
      J

      Johns Hopkins University

      Business Analytics with Excel: Elementary to Advanced

      Skills you'll gain: Risk Modeling, Operations Research, Regression Analysis, Microsoft Excel, Business Analytics, Risk Analysis, Business Process Modeling, Business Modeling, Data Modeling, Resource Allocation, Statistical Analysis, Process Optimization, Financial Analysis, Predictive Analytics, Transportation Operations, Complex Problem Solving, Linear Algebra

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • D

      Duke University

      Inferential Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Reporting, Statistical Methods, R Programming, Statistical Software, Statistical Analysis, Probability & Statistics, Data Literacy, Sampling (Statistics), Probability Distribution, Software Installation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.7K reviews

      Beginner · Course · 1 - 3 Months

    • M

      Macquarie University

      Excel Regression Models for Business Forecasting

      Skills you'll gain: Forecasting, Regression Analysis, Time Series Analysis and Forecasting, Business Mathematics, Microsoft Excel, Statistical Modeling, Trend Analysis, Statistical Analysis, Data Visualization Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      108 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Virginia

      Marketing Analytics

      Skills you'll gain: Marketing Analytics, Marketing Effectiveness, Marketing, Marketing Strategies, Regression Analysis, Data-Driven Decision-Making, Strategic Marketing, Brand Management, Resource Allocation, Customer Insights, Predictive Analytics, Advertising Campaigns, Statistical Analysis, A/B Testing, Consumer Behaviour, Return On Investment

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.4K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Washington

      Machine Learning: Regression

      Skills you'll gain: Regression Analysis, Predictive Modeling, Supervised Learning, Statistical Modeling, Applied Machine Learning, Predictive Analytics, Feature Engineering, Machine Learning, Statistical Methods, Python Programming, Data Manipulation, Linear Algebra, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.6K reviews

      Mixed · Course · 1 - 3 Months

    Logistic Regression learners also search

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    Predictive Modeling
    Statistical Modeling
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    1…678…45

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

    • Machine Learning: University of Washington
    • Business Statistics and Analysis: Rice University
    • Mathematics for Machine Learning: Multivariate Calculus: Imperial College London
    • Bayesian Statistics: University of California, Santa Cruz
    • Introduction to Spreadsheets and Models: University of Pennsylvania
    • Data Science: Statistics and Machine Learning: Johns Hopkins University
    • Advanced Linear Models for Data Science 1: Least Squares: Johns Hopkins University
    • Business Analytics with Excel: Elementary to Advanced: Johns Hopkins University
    • Inferential Statistics: Duke University
    • Excel Regression Models for Business Forecasting: Macquarie University

    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 Logistic Regression

    Logistic regression is a technique used in statistics that allows people to estimate the probability of something happening based on existing data they have about that event taking place before. Mathematical models are used often in science and engineering disciplines to explain concepts using mathematical language, and one of these models is logical regression. Logistic regression works using binary data, meaning there are only two possible outcomes for the event: It takes place, or it doesn’t take place. To figure out the probability of these two outcomes, logistic regression uses equations that calculate odds ratios — the odds that something will happen or it won’t. This predictive modeling tool plays a large role not only in statistics but also in machine learning, which involves computers learning information that they haven’t explicitly been programmed to process.‎

    If you’re considering going into a career field that works with data, software or mathematics, logical regression is a valuable area of study to focus on. Logistic regression becomes an important step of the programming process when you’re building software that deals with predictive modeling or data analysis. And, if you’re interested in enhancing your understanding of machine learning, logistic regression is an essential. When you understand modeling with logical regression, you can progress more easily to the complex models involved with machine learning while learning how to best prepare data for processing.‎

    A career as a data scientist or data analyst gives you the opportunity to apply your knowledge of logistic regression, but you’ll also frequently draw upon your skills in this arena if you want to go into the field of machine learning. Although these careers are relatively broad, working with machine learning and logistic regression is also possible in a variety of specialties you’ll find in software engineering, computational linguistics and software development. As you begin to learn more about logistic regression while taking online classes, you may discover a particular area of interest you want to explore — and your new skills can help you discover more.‎

    Taking online courses about logistic regression can give you the knowledge you need to progress in your field or start fresh. In your career as a data scientist or analyst, you know the importance of statistical approaches and the variety of data-modeling techniques you utilize on a regular basis. But if you’re ready to dig deeper into these concepts to boost your understanding and put new ideas and skills into practice, taking online courses about logistic regression can get you where you want to go. If you’re starting with the basics, take a ground-up approach with introductory courses that create a solid foundation for future learning. Or, if you’re looking to supplement your existing knowledge base with a greater understanding of logistic regression, try courses that help you learn the concept’s role in machine learning and programming software for predictive modeling. You’ll appreciate your newfound comprehension of these innovative ideas — and you’ll love the freedom to participate in online courses when and where it’s most convenient for you.‎

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

    When looking to enhance your workforce's skills in Logistic 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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