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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

    • C

      Coursera Project Network

      Data Analysis in R: Predictive Analysis with Regression

      Skills you'll gain: Ggplot2, Data Visualization, Regression Analysis, Predictive Analytics, Data-Driven Decision-Making, Statistical Modeling, R Programming, Descriptive Statistics, Exploratory Data Analysis, Statistics

      4.2
      Rating, 4.2 out of 5 stars
      ·
      13 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      Mining Quality Prediction Using Machine & Deep Learning

      Skills you'll gain: Regression Analysis, Predictive Modeling, Exploratory Data Analysis, Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Decision Tree Learning, Statistical Analysis, Data Analysis, Test Data, Artificial Neural Networks, Data Import/Export, Pandas (Python Package), Software Visualization

      4.8
      Rating, 4.8 out of 5 stars
      ·
      66 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      Build a Machine Learning Web App with Streamlit and Python

      Skills you'll gain: Machine Learning Algorithms, Data Visualization, Dashboard, Interactive Data Visualization, Data Visualization Software, Applied Machine Learning, Machine Learning, Scikit Learn (Machine Learning Library), Web Applications, Predictive Modeling, Classification And Regression Tree (CART), Python Programming, Pandas (Python Package)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      405 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Foundations of Sports Analytics: Data, Representation, and Models in Sports

      Skills you'll gain: Statistical Methods, Regression Analysis, Data Cleansing, Statistical Hypothesis Testing, Correlation Analysis, Matplotlib, Data Manipulation, Data Visualization, Statistical Analysis, Scatter Plots, Probability & Statistics, R Programming, Data Analysis, Descriptive Statistics, Pandas (Python Package), Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      187 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis with R

      Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Analysis, Data Transformation, R Programming, Data Manipulation, Data Visualization, Box Plots, Predictive Analytics, Statistical Analysis, Regression Analysis, Statistical Modeling, Correlation Analysis, Data Cleansing, Tidyverse (R Package), Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      334 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Meta

      Data Analytics Methods for Marketing

      Skills you'll gain: Marketing Analytics, Marketing Effectiveness, A/B Testing, Target Audience, Marketing Strategies, Marketing, Marketing Planning, Sales Pipelines, Customer Analysis, Marketing Channel, Advertising Campaigns, Regression Analysis, Forecasting, Unsupervised Learning, Key Performance Indicators (KPIs), Return On Investment

      4.7
      Rating, 4.7 out of 5 stars
      ·
      264 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      E

      Emory University

      Meaningful Marketing Insights

      Skills you'll gain: Pivot Tables And Charts, Marketing Analytics, Descriptive Statistics, Microsoft Excel, Customer Insights, Regression Analysis, Data Analysis, Data-Driven Decision-Making, Marketing, Marketing Effectiveness, Exploratory Data Analysis, Consumer Behaviour, Statistical Analysis, Data Manipulation

      4.3
      Rating, 4.3 out of 5 stars
      ·
      284 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Meaningful Predictive Modeling

      Skills you'll gain: Predictive Modeling, Data Validation, Verification And Validation, Applied Machine Learning, Regression Analysis, Supervised Learning, Classification And Regression Tree (CART), Python Programming, Statistical Methods, Scikit Learn (Machine Learning Library), Text Mining, Test Data, Natural Language Processing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      48 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Introduction to Machine Learning: Supervised Learning

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Decision Tree Learning, Scikit Learn (Machine Learning Library), Matplotlib, Random Forest Algorithm, Machine Learning, Predictive Modeling, Data Science, Classification And Regression Tree (CART), Python Programming, Mathematical Modeling, Applied Mathematics, Exploratory Data Analysis, Statistical Programming, Regression Analysis, Feature Engineering, Data Cleansing, Performance Tuning

      Build toward a degree

      3.4
      Rating, 3.4 out of 5 stars
      ·
      76 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Azure Machine Learning

      Skills you'll gain: Unsupervised Learning, Microsoft Azure, Applied Machine Learning, Regression Analysis, Predictive Modeling, Machine Learning Methods, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Artificial Intelligence, Automation, Supervised Learning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      232 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      Universidad de los Andes

      Fundamentos de estadística aplicada

      Skills you'll gain: Statistical Hypothesis Testing, Descriptive Statistics, Statistical Methods, Data Analysis, Regression Analysis, Sampling (Statistics), Statistical Analysis, Probability & Statistics, Probability Distribution, Applied Mathematics, Statistical Inference

      4.5
      Rating, 4.5 out of 5 stars
      ·
      134 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      V

      Vanderbilt University

      Introduction to Data, Signal, and Image Analysis with MATLAB

      Skills you'll gain: Data Visualization, Image Analysis, Data Visualization Software, Machine Learning Methods, Matlab, Applied Machine Learning, Statistical Methods, Data Analysis, Data Processing, Computer Vision, Regression Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      219 reviews

      Intermediate · Course · 1 - 3 Months

    Logistic Regression learners also search

    Regression
    Regression Analysis
    Regression Models
    Linear Regression
    Predictive Modeling
    Statistical Modeling
    Predictive Analytics
    Data Modeling
    1…151617…45

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

    • Data Analysis in R: Predictive Analysis with Regression: Coursera Project Network
    • Mining Quality Prediction Using Machine & Deep Learning: Coursera Project Network
    • Build a Machine Learning Web App with Streamlit and Python: Coursera Project Network
    • Foundations of Sports Analytics: Data, Representation, and Models in Sports: University of Michigan
    • Data Analysis with R: IBM
    • Data Analytics Methods for Marketing: Meta
    • Meaningful Marketing Insights: Emory University
    • Meaningful Predictive Modeling: University of California San Diego
    • Introduction to Machine Learning: Supervised Learning: University of Colorado Boulder
    • Microsoft Azure Machine Learning: Microsoft

    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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