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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 California San Diego

      Deploying Machine Learning Models

      Skills you'll gain: Data Manipulation, Applied Machine Learning, Flask (Web Framework), Application Deployment, Django (Web Framework), Web Applications, Data Processing, Predictive Modeling, Machine Learning, Regression Analysis

      3.5
      Rating, 3.5 out of 5 stars
      ·
      51 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Predicción de Ventas Pronosticando Tendencias

      Skills you'll gain: Forecasting, Trend Analysis, Spreadsheet Software, Predictive Analytics, Regression Analysis, Time Series Analysis and Forecasting, Data Visualization, Statistical Methods, Statistical Analysis, Plot (Graphics), Data-Driven Decision-Making, Data Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      110 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: New
      New
      J

      Johns Hopkins University

      Foundational Mathematics for AI

      Skills you'll gain: Descriptive Statistics, Linear Algebra, Exploratory Data Analysis, Data-Driven Decision-Making, Bayesian Statistics, Statistics, Artificial Intelligence and Machine Learning (AI/ML), Probability, Regression Analysis, Calculus, Statistical Analysis, Advanced Mathematics, Applied Mathematics, Probability Distribution, Mathematical Modeling, Integral Calculus, Algebra, Machine Learning Algorithms, Dimensionality Reduction, Correlation Analysis

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Cervical Cancer Risk Prediction Using Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Data Analysis, Statistical Analysis, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Predictive Modeling, Matplotlib, Data Import/Export, Pandas (Python Package), Applied Machine Learning, Data Visualization Software, NumPy, Data Manipulation, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      38 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      S

      SkillUp EdTech

      The Business Intelligence (BI) Analyst Capstone Project

      Skills you'll gain: Presentations, Business Intelligence, Dashboard, Tableau Software, IBM Cognos Analytics, Statistical Analysis, Data Analysis, Looker (Software), Regression Analysis, PostgreSQL, Microsoft PowerPoint, Pivot Tables And Charts, Data Visualization Software, Data Cleansing, Microsoft Excel, SQL, Data Manipulation, LinkedIn, Data Quality

      4.7
      Rating, 4.7 out of 5 stars
      ·
      34 reviews

      Advanced · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      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

    • C

      Coursera Project Network

      Solving ML Regression Problems with AWS AutoGluon

      Skills you'll gain: AWS SageMaker, Applied Machine Learning, Predictive Modeling, Machine Learning, Machine Learning Algorithms, Amazon Web Services, Regression Analysis

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      U

      University of Illinois Urbana-Champaign

      Machine Learning for Accounting with Python

      Skills you'll gain: Machine Learning Algorithms, Unsupervised Learning, Scikit Learn (Machine Learning Library), Machine Learning, Text Mining, Applied Machine Learning, Time Series Analysis and Forecasting, Data Processing, Supervised Learning, Predictive Modeling, Python Programming, Regression Analysis, Feature Engineering, Jupyter, Pandas (Python Package), Natural Language Processing, Statistical Analysis, Performance Metric

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      43 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Toronto

      Inclusive Analytic Techniques

      Skills you'll gain: Data Ethics, Data Collection, Quantitative Research, Qualitative Research, Data Analysis, Statistical Analysis, Analytics, Regression Analysis, Research, Focus Group, Correlation Analysis, Diversity and Inclusion, Surveys, Probability, Stakeholder Engagement

      4.8
      Rating, 4.8 out of 5 stars
      ·
      78 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      B

      Board Infinity

      Essential Testing Techniques in Software Development

      Skills you'll gain: Test Case, Software Testing, Integration Testing, Software Development Life Cycle, System Testing, Acceptance Testing, Maintainability, Regression Testing, Test Planning, Software Quality Assurance, Unit Testing, Functional Testing, User Acceptance Testing (UAT)

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7 reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      Packt

      Regression Analysis for Statistics & Machine Learning in R

      Skills you'll gain: Regression Analysis, Data Cleansing, R Programming, Applied Machine Learning, Statistical Analysis, Data Manipulation, Statistical Machine Learning, Classification And Regression Tree (CART), Tidyverse (R Package), Advanced Analytics, Statistical Modeling, Random Forest Algorithm, Data Transformation, Statistical Methods, Predictive Modeling, Exploratory Data Analysis, Feature Engineering, Machine Learning, Dimensionality Reduction

      Intermediate · Course · 1 - 3 Months

    • S

      S.P. Jain Institute of Management and Research

      Data Analysis

      Skills you'll gain: Data Analysis, Quantitative Research, Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Business Analytics, Regression Analysis, Business Mathematics, Data-Driven Decision-Making, Statistical Analysis, Probability Distribution, Microsoft Excel, Statistical Inference, Probability, Variance Analysis, Estimation

      Build toward a degree

      5
      Rating, 5 out of 5 stars
      ·
      7 reviews

      Beginner · Course · 1 - 3 Months

    Logistic Regression learners also search

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    Predictive Modeling
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    1…272829…45

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

    • Deploying Machine Learning Models: University of California San Diego
    • Predicción de Ventas Pronosticando Tendencias : Coursera Project Network
    • Foundational Mathematics for AI: Johns Hopkins University
    • Cervical Cancer Risk Prediction Using Machine Learning: Coursera Project Network
    • The Business Intelligence (BI) Analyst Capstone Project: SkillUp EdTech
    • Supervised Learning Regression Classification Clustering: Simplilearn
    • Solving ML Regression Problems with AWS AutoGluon: Coursera Project Network
    • Machine Learning for Accounting with Python: University of Illinois Urbana-Champaign
    • Inclusive Analytic Techniques: University of Toronto
    • Essential Testing Techniques in Software Development: Board Infinity

    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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