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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 Colorado Boulder

      Regression Analysis

      Skills you'll gain: Regression Analysis, Supervised Learning, Scikit Learn (Machine Learning Library), Statistical Analysis, Data Analysis, Statistical Modeling, Predictive Modeling, Machine Learning Methods, Feature Engineering, Exploratory Data Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 3 Months

    • 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

    • E

      EIT Digital

      Data Science for Business Innovation

      Skills you'll gain: Data-Driven Decision-Making, Big Data, Data Science, NoSQL, Data Modeling, Data Storage Technologies, Analytics, Business Analytics, Data Mining, Data Analysis, Machine Learning, Unsupervised Learning, Regression Analysis, Classification And Regression Tree (CART), Descriptive Analytics, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML)

      4.3
      Rating, 4.3 out of 5 stars
      ·
      264 reviews

      Beginner · Course · 1 - 4 Weeks

    • 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
      ·
      404 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • M

      Microsoft

      Create Machine Learning Models in Microsoft Azure

      Skills you'll gain: Unsupervised Learning, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Exploratory Data Analysis, Deep Learning, Microsoft Azure, Data Visualization, Applied Machine Learning, Regression Analysis, Predictive Modeling, Data Analysis, Image Analysis, Pandas (Python Package), Artificial Intelligence and Machine Learning (AI/ML), Data Science, MLOps (Machine Learning Operations), Machine Learning, Supervised Learning, Tensorflow, NumPy

      4.5
      Rating, 4.5 out of 5 stars
      ·
      292 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Illinois Urbana-Champaign

      Applying Data Analytics in Finance

      Skills you'll gain: Time Series Analysis and Forecasting, Portfolio Management, Financial Forecasting, Financial Analysis, Analytics, Financial Trading, Financial Market, Performance Analysis, Statistical Analysis, Investment Management, Risk Management, Regression Analysis, Algorithms

      4.4
      Rating, 4.4 out of 5 stars
      ·
      216 reviews

      Intermediate · Course · 1 - 3 Months

    • S

      SAS

      Statistical Thinking for Industrial Problem Solving, presented by JMP

      Skills you'll gain: Exploratory Data Analysis, Data Compilation, Correlation Analysis, Data Collection, Statistical Inference, Statistical Methods, Statistical Modeling, Predictive Modeling, Data Analysis, Data-Driven Decision-Making, Regression Analysis, Statistical Analysis, Probability & Statistics, Statistical Visualization

      4.9
      Rating, 4.9 out of 5 stars
      ·
      92 reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      U

      University of Illinois Urbana-Champaign

      Introduction to Artificial Intelligence

      Skills you'll gain: Generative AI, Applied Machine Learning, Deep Learning, Artificial Intelligence, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Unsupervised Learning, Regression Analysis, Emerging Technologies, Law, Regulation, and Compliance, Business Analytics, Governance

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      15 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      CertNexus

      Build Regression, Classification, and Clustering Models

      Skills you'll gain: Unsupervised Learning, Regression Analysis, Machine Learning Algorithms, Linear Algebra, Machine Learning, Predictive Modeling, Statistical Methods, Supervised Learning, Feature Engineering, Classification And Regression Tree (CART), Performance Tuning, Algorithms

      4.4
      Rating, 4.4 out of 5 stars
      ·
      16 reviews

      Intermediate · Course · 1 - 3 Months

    • R

      Rutgers the State University of New Jersey

      Demand Analytics

      Skills you'll gain: Demand Planning, Data Collection, Forecasting, Supply Chain Planning, Statistical Modeling, Data Processing, Market Dynamics, Time Series Analysis and Forecasting, Trend Analysis, Regression Analysis, Exploratory Data Analysis, Data Validation, Data Analysis Software

      4.6
      Rating, 4.6 out of 5 stars
      ·
      289 reviews

      Beginner · Course · 1 - 4 Weeks

    • 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

    • 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
      ·
      218 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…161718…44

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

    • Regression Analysis: University of Colorado Boulder
    • Meaningful Predictive Modeling: University of California San Diego
    • Data Science for Business Innovation: EIT Digital
    • Build a Machine Learning Web App with Streamlit and Python: Coursera Project Network
    • Create Machine Learning Models in Microsoft Azure: Microsoft
    • Applying Data Analytics in Finance: University of Illinois Urbana-Champaign
    • Statistical Thinking for Industrial Problem Solving, presented by JMP: SAS
    • Introduction to Artificial Intelligence: University of Illinois Urbana-Champaign
    • Build Regression, Classification, and Clustering Models: CertNexus
    • Demand Analytics: Rutgers the State University of New Jersey

    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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