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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

    • E

      EDHEC Business School

      Python and Machine Learning for Asset Management

      Skills you'll gain: Investment Management, Portfolio Management, Asset Management, Machine Learning, Applied Machine Learning, Financial Modeling, Supervised Learning, Predictive Modeling, Risk Management, Feature Engineering, Unsupervised Learning, Regression Analysis, Statistical Methods, Dimensionality Reduction

      3.1
      Rating, 3.1 out of 5 stars
      ·
      328 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Applying Data Analytics in Marketing

      Skills you'll gain: Marketing Analytics, Regression Analysis, Network Analysis, Market Analysis, Analytics, Statistical Analysis, Customer Insights, Data Analysis, Statistical Methods, Text Mining, Unstructured Data, Social Media, Natural Language Processing

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      187 reviews

      Intermediate · Course · 1 - 4 Weeks

    • F

      Fundação Instituto de Administração

      Data & Finance for the future

      Skills you'll gain: Financial Statement Analysis, Financial Statements, Financial Analysis, Business Analytics, Regression Analysis, Business Valuation, Descriptive Statistics, Data Analysis, Data-Driven Decision-Making, Statistical Inference, Financial Accounting, Cash Flows, Balance Sheet, Income Statement, Competitive Analysis, International Finance, Business Economics, Economics, Market Dynamics, Business Planning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      447 reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Principles of fMRI 2

      Skills you'll gain: Magnetic Resonance Imaging, Data Analysis, Analysis, Image Analysis, Statistical Analysis, Experimentation, Network Analysis, Research Design, Regression Analysis, Psychology, Time Series Analysis and Forecasting, Matlab, Mental and Behavioral Health, Neurology, Statistical Modeling, Statistical Methods, Research

      4.7
      Rating, 4.7 out of 5 stars
      ·
      245 reviews

      Mixed · Course · 1 - 4 Weeks

    • 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
      ·
      332 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      P

      Pontificia Universidad Católica de Chile

      Introducción a los modelos de demanda de transporte

      Skills you'll gain: Data Collection, Transportation Operations, Surveys, Quantitative Research, Mathematical Modeling, Predictive Modeling, Statistical Methods, Regression Analysis, Spatial Analysis, Probability Distribution, Probability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      458 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Generalized Linear Models and Nonparametric Regression

      Skills you'll gain: Statistical Modeling, R Programming, Data Analysis, Data Ethics, Advanced Analytics, Statistical Methods, Regression Analysis, Machine Learning, Classification And Regression Tree (CART), Statistical Inference, Probability Distribution

      Build toward a degree

      4.3
      Rating, 4.3 out of 5 stars
      ·
      20 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Predictive Analytics for Business with H2O in R

      Skills you'll gain: R Programming, Predictive Analytics, Applied Machine Learning, Data Science, Data Processing, Feature Engineering, Machine Learning, Telemarketing, Application Deployment

      4.9
      Rating, 4.9 out of 5 stars
      ·
      52 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • 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
      ·
      133 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      D

      Duke University

      Programming for Python Data Science: Principles to Practice

      Skills you'll gain: Matplotlib, Pandas (Python Package), NumPy, Computational Thinking, Predictive Modeling, Data Cleansing, Data Structures, Data Visualization Software, Visualization (Computer Graphics), Debugging, Data Analysis, Object Oriented Programming (OOP), Data Manipulation, Regression Analysis, Python Programming, Data Science, Algorithms, Simulations, Statistical Methods, Program Development

      3.8
      Rating, 3.8 out of 5 stars
      ·
      65 reviews

      Beginner · Specialization · 3 - 6 Months

    • 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
      ·
      186 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Scikit-Learn to Solve Regression Machine Learning Problems

      Skills you'll gain: Scikit Learn (Machine Learning Library), Predictive Modeling, Regression Analysis, Machine Learning Algorithms, Applied Machine Learning, Python Programming, Machine Learning, Random Forest Algorithm

      Beginner · Guided Project · Less Than 2 Hours

    Logistic Regression learners also search

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    1…171819…44

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

    • Python and Machine Learning for Asset Management : EDHEC Business School
    • Applying Data Analytics in Marketing: University of Illinois Urbana-Champaign
    • Data & Finance for the future: Fundação Instituto de Administração
    • Principles of fMRI 2: Johns Hopkins University
    • Data Analysis with R: IBM
    • Introducción a los modelos de demanda de transporte: Pontificia Universidad Católica de Chile
    • Generalized Linear Models and Nonparametric Regression: University of Colorado Boulder
    • Predictive Analytics for Business with H2O in R: Coursera Project Network
    • Fundamentos de estadística aplicada: Universidad de los Andes
    • Programming for Python Data Science: Principles to Practice: Duke 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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