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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

    • Status: Free Trial
      Free Trial
      U

      University of London

      Data Science Project Capstone: Predicting Bicycle Rental

      Skills you'll gain: Correlation Analysis, Predictive Modeling, Data Collection, Regression Analysis, Data Science, Forecasting, Data Analysis, Statistical Modeling, Time Series Analysis and Forecasting, Data-Driven Decision-Making, Exploratory Data Analysis

      4.2
      Rating, 4.2 out of 5 stars
      ·
      10 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      From Data To Decision With AI

      Skills you'll gain: Statistical Methods, Data Presentation, Regression Analysis, Generative AI, Data Literacy, Statistical Analysis, Data-Driven Decision-Making, Technical Communication, Probability & Statistics, Data Analysis, Exploratory Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Predictive Analytics, Data Storytelling, Box Plots, Analytical Skills, Artificial Intelligence, Plot (Graphics), Forecasting

      4.4
      Rating, 4.4 out of 5 stars
      ·
      9 reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science Decisions in Time: Using Data Effectively

      Skills you'll gain: Reinforcement Learning, Data-Driven Decision-Making, Decision Tree Learning, Markov Model, Data Analysis, Time Series Analysis and Forecasting, Bayesian Statistics, Statistical Methods, Anomaly Detection, Probability Distribution, Machine Learning Methods, Statistical Analysis, Sampling (Statistics)

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      U

      University of Michigan

      Statistics with Python Using NumPy, Pandas, and SciPy

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Probability & Statistics, NumPy, Statistical Methods, Probability, Statistics, Probability Distribution, Statistical Analysis, Data Analysis, Histogram, Scatter Plots, Regression Analysis, Pandas (Python Package), Linear Algebra

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      C

      CertNexus

      Train Machine Learning Models

      Skills you'll gain: Jupyter, Unsupervised Learning, Classification And Regression Tree (CART), Applied Machine Learning, Predictive Modeling, Regression Analysis, Machine Learning, Supervised Learning, Statistical Modeling, Machine Learning Algorithms, Performance Tuning, Performance Metric, Algorithms

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      S

      SAS

      Modeling Time Series and Sequential Data

      Skills you'll gain: Time Series Analysis and Forecasting, SAS (Software), Forecasting, Regression Analysis, Applied Machine Learning, Statistical Analysis, Advanced Analytics, Statistical Methods, Predictive Modeling, Statistical Modeling, Bayesian Statistics, Artificial Neural Networks

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Trees, SVM and Unsupervised Learning

      Skills you'll gain: Applied Machine Learning, Supervised Learning, Statistical Machine Learning, Data Science, Artificial Neural Networks, Dimensionality Reduction, Unsupervised Learning, Classification And Regression Tree (CART), Machine Learning Algorithms, Decision Tree Learning, Machine Learning, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Feature Engineering, Random Forest Algorithm

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Resampling, Selection and Splines

      Skills you'll gain: Data Science, R Programming, Statistical Machine Learning, Advanced Analytics, Dimensionality Reduction, Statistical Modeling, Statistical Analysis, Statistical Methods, Sampling (Statistics), Regression Analysis, Statistical Inference

      5
      Rating, 5 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Data Analysis with Python Project

      Skills you'll gain: Dimensionality Reduction, Data Analysis, Supervised Learning, Anomaly Detection, Machine Learning, Machine Learning Algorithms, Statistical Analysis, Unsupervised Learning, Data Mining, Analytics, Predictive Modeling, Regression Analysis, Scikit Learn (Machine Learning Library), Classification And Regression Tree (CART), Exploratory Data Analysis, Statistical Methods

      5
      Rating, 5 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      H

      Howard University

      Business Modeling Tools

      Skills you'll gain: Regression Analysis, Data-Driven Decision-Making, Business Modeling, Business Analytics, Statistical Analysis, Spreadsheet Software, Forecasting, Data Analysis, Microsoft Excel, Predictive Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      Università di Napoli Federico II

      Development Economics

      Skills you'll gain: Economic Development, Economics, Human Capital, Policy Analysis, Econometrics, Program Evaluation, Social Sciences, Behavioral Economics, Analysis, Financial Analysis, Entrepreneurship, Insurance, Regression Analysis

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      Università di Napoli Federico II

      Machine Learning e Data Mining in R

      Skills you'll gain: Unsupervised Learning, Supervised Learning, R Programming, Artificial Neural Networks, Machine Learning, Exploratory Data Analysis, Data Mining, Tidyverse (R Package), Deep Learning, Predictive Modeling, Ggplot2, Regression Analysis, Dimensionality Reduction, Data Analysis, Statistical Analysis, Data Visualization Software, Data Manipulation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      9 reviews

      Intermediate · Course · 1 - 4 Weeks

    Logistic Regression learners also search

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    1…363738…45

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

    • Data Science Project Capstone: Predicting Bicycle Rental: University of London
    • From Data To Decision With AI: Vanderbilt University
    • Data Science Decisions in Time: Using Data Effectively: Johns Hopkins University
    • Statistics with Python Using NumPy, Pandas, and SciPy: University of Michigan
    • Train Machine Learning Models: CertNexus
    • Modeling Time Series and Sequential Data: SAS
    • Trees, SVM and Unsupervised Learning: University of Colorado Boulder
    • Resampling, Selection and Splines: University of Colorado Boulder
    • Data Analysis with Python Project : University of Colorado Boulder
    • Business Modeling Tools: Howard 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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