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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 Michigan

      Linear Regression Modeling for Health Data

      Skills you'll gain: Statistical Modeling, Regression Analysis, Statistical Methods, Statistical Inference, Probability & Statistics, Correlation Analysis, Data Analysis, Statistical Analysis, Statistical Hypothesis Testing, Predictive Modeling

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      N

      National Taiwan University

      人工智慧:機器學習與理論基礎 (Artificial Intelligence - Learning & Theory)

      Skills you'll gain: Reinforcement Learning, Deep Learning, Theoretical Computer Science, Artificial Neural Networks, Artificial Intelligence, Classification And Regression Tree (CART), Machine Learning, Supervised Learning, Computer Science, Unsupervised Learning, Algorithms, Network Architecture

      4.6
      Rating, 4.6 out of 5 stars
      ·
      59 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      S

      Sungkyunkwan University

      Machine Learning Basics

      Skills you'll gain: Machine Learning Algorithms, Machine Learning, Python Programming, Supervised Learning, Scikit Learn (Machine Learning Library), Applied Machine Learning, Regression Analysis, Data Analysis, Statistical Methods, Linear Algebra, Probability

      4.3
      Rating, 4.3 out of 5 stars
      ·
      69 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: New
      New
      A

      American Psychological Association

      Basic Inferential Statistics for Psychology

      Skills you'll gain: Sample Size Determination, Statistical Hypothesis Testing, Probability & Statistics, Statistical Methods, Probability Distribution, Quantitative Research, Statistical Analysis, Statistical Software, Statistical Inference, Sampling (Statistics), Data Analysis, Statistics, Analytical Skills, Data Literacy, Psychology, Research Design, Research

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      C

      Columbia University

      Causal Inference

      Skills you'll gain: Statistical Inference, Regression Analysis, Statistical Methods, Estimation, Machine Learning, Statistical Modeling, Experimentation, Data Collection, Probability & Statistics, Research Design, Program Evaluation, Decision Making

      3.4
      Rating, 3.4 out of 5 stars
      ·
      98 reviews

      Advanced · Course · 1 - 3 Months

    • W

      Wesleyan University

      Data Analysis Tools

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Statistical Software, Correlation Analysis, SAS (Software), Data Analysis, Statistical Methods, Quantitative Research, Probability & Statistics, Analytical Skills, Regression Analysis, Data Management, Statistical Inference

      4.5
      Rating, 4.5 out of 5 stars
      ·
      414 reviews

      Mixed · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Support Vector Machines in Python, From Start to Finish

      Skills you'll gain: Scikit Learn (Machine Learning Library), Tensorflow, Cloud Computing, Classification And Regression Tree (CART), Supervised Learning, Applied Machine Learning, Machine Learning Methods, Pandas (Python Package), Data Visualization, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      155 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • I

      IBM

      Statistical Analysis Fundamentals using Excel

      Skills you'll gain: Descriptive Statistics, Regression Analysis, Forecasting, Probability Distribution, Business Analytics, Data Analysis, Statistical Analysis, Statistical Methods, Microsoft Excel, Statistics, Spreadsheet Software, Predictive Analytics, Probability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      89 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Essential Causal Inference Techniques for Data Science

      Skills you'll gain: Regression Analysis, Data Science, Statistical Machine Learning, Data-Driven Decision-Making, R Programming, Statistical Inference, Applied Machine Learning, Classification And Regression Tree (CART), Machine Learning, Statistical Methods, Advanced Analytics, Data Analysis, Predictive Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      38 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: New
      New
      S

      Simplilearn

      Supervised Learning Regression Classification Clustering

      Skills you'll gain: Supervised Learning, Data Modeling, Data Analysis, Regression Analysis, Unsupervised Learning, Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Predictive Modeling, Predictive Analytics, Random Forest Algorithm, Bayesian Statistics

      Beginner · Course · 1 - 4 Weeks

    • S

      SkillUp EdTech

      ASQ-Certified Six Sigma Black Belt (CSSBB) Exam Prep

      Skills you'll gain: Statistical Process Controls, Statistical Hypothesis Testing, Lean Methodologies, Team Motivation, Process Improvement, Six Sigma Methodology, Kaizen Methodology, Process Capability, Risk Analysis, Team Leadership, Quality Improvement, Team Management, Benchmarking, Motivational Skills, Performance Measurement, Change Management, Process Analysis, Statistical Analysis, Continuous Improvement Process, Organizational Change

      4.8
      Rating, 4.8 out of 5 stars
      ·
      28 reviews

      Intermediate · Specialization · 1 - 3 Months

    • T

      The University of Chicago

      Machine Learning: Concepts and Applications

      Skills you'll gain: Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Classification And Regression Tree (CART), Decision Tree Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Supervised Learning, Regression Analysis, Random Forest Algorithm, Dimensionality Reduction, Statistical Methods, Tensorflow, Feature Engineering, Artificial Neural Networks, Pandas (Python Package)

      3.9
      Rating, 3.9 out of 5 stars
      ·
      22 reviews

      Intermediate · Course · 1 - 3 Months

    Logistic Regression learners also search

    Regression
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    Regression Models
    Linear Regression
    Predictive Modeling
    Statistical Modeling
    Predictive Analytics
    Data Modeling
    1…212223…44

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

    • Linear Regression Modeling for Health Data: University of Michigan
    • 人工智慧:機器學習與理論基礎 (Artificial Intelligence - Learning & Theory): National Taiwan University
    • Machine Learning Basics: Sungkyunkwan University
    • Basic Inferential Statistics for Psychology: American Psychological Association
    • Causal Inference: Columbia University
    • Data Analysis Tools: Wesleyan University
    • Support Vector Machines in Python, From Start to Finish: Coursera Project Network
    • Statistical Analysis Fundamentals using Excel: IBM
    • Essential Causal Inference Techniques for Data Science: Coursera Project Network
    • Supervised Learning Regression Classification Clustering: Simplilearn

    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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