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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

    • S

      SAS

      Introduction to Statistical Analysis: Hypothesis Testing

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, SAS (Software), Regression Analysis, Exploratory Data Analysis, Statistical Methods, Probability & Statistics, Statistical Modeling, Plot (Graphics), Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      166 reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      MathWorks

      Practical Data Science with MATLAB

      Skills you'll gain: Data Storytelling, Feature Engineering, Data Visualization, Supervised Learning, Dimensionality Reduction, Data Integration, Interactive Data Visualization, Exploratory Data Analysis, Data Import/Export, Technical Communication, Data Analysis, Applied Machine Learning, Data Visualization Software, Matlab, Regression Analysis, Data Processing, Descriptive Statistics, Data Cleansing, Predictive Modeling, Data Science

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Launching into Machine Learning

      Skills you'll gain: Data Quality, Exploratory Data Analysis, Machine Learning, MLOps (Machine Learning Operations), Applied Machine Learning, Scikit Learn (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Google Cloud Platform, Machine Learning Algorithms, Data Analysis, Predictive Modeling, Big Data, Classification And Regression Tree (CART), Regression Analysis, Data Processing, Sampling (Statistics), Test Data, Performance Tuning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.3K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Santa Cruz

      Bayesian Statistics: Techniques and Models

      Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Markov Model, Statistical Analysis, Regression Analysis, R Programming, Simulations, Statistical Inference, Data Analysis, Probability, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      489 reviews

      Intermediate · Course · 1 - 3 Months

    • Q

      Queen Mary University of London

      Market Research

      Skills you'll gain: Qualitative Research, Proposal Development, Market Research, Research Reports, Data Collection, Research Design, Research Methodologies, Data Analysis, Statistical Hypothesis Testing, Survey Creation, Statistical Analysis, Surveys, Correlation Analysis, Quantitative Research, Research, Science and Research, Market Analysis, Focus Group, Regression Analysis, Content Performance Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      432 reviews

      Beginner · Specialization · 3 - 6 Months

    • W

      Wesleyan University

      Data Analysis and Interpretation

      Skills you'll gain: Regression Analysis, Data Storytelling, Classification And Regression Tree (CART), Statistical Hypothesis Testing, Descriptive Statistics, Data Presentation, Statistical Analysis, Statistical Software, Correlation Analysis, Exploratory Data Analysis, Data Manipulation, Decision Tree Learning, Data Management, Data Analysis, Predictive Modeling, Data Visualization, Data Literacy, Random Forest Algorithm, SAS (Software), Statistical Modeling

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.4K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Accounting Data Analytics

      Skills you'll gain: Machine Learning Algorithms, Jupyter, Tableau Software, Matplotlib, Data Visualization Software, Unsupervised Learning, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data Manipulation, Machine Learning, Excel Macros, Text Mining, Applied Machine Learning, Time Series Analysis and Forecasting, Data Processing, Analytics, SQL, Supervised Learning, Accounting and Finance Software, Specialized Accounting

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      562 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Sports Performance Analytics

      Skills you'll gain: Forecasting, Statistical Methods, Regression Analysis, Data Cleansing, Scikit Learn (Machine Learning Library), Supervised Learning, Data Processing, Statistical Hypothesis Testing, Correlation Analysis, Predictive Analytics, Predictive Modeling, Matplotlib, Applied Machine Learning, Kinesiology, Injury Prevention, Statistical Machine Learning, Analytics, Data Analysis, Statistical Analysis, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      255 reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Precalculus through Data and Modelling

      Skills you'll gain: Data Analysis, Applied Mathematics, Mathematical Modeling, Graphing, Trigonometry, Analytical Skills, R Programming, General Mathematics, Statistics, Algebra, Systems Of Measurement, Correlation Analysis, Regression Analysis, Calculus, Geometry

      4.7
      Rating, 4.7 out of 5 stars
      ·
      303 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      N

      National Taiwan University

      機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

      Skills you'll gain: Supervised Learning, Machine Learning, Classification And Regression Tree (CART), Theoretical Computer Science, Applied Mathematics, Mathematical Modeling, Probability & Statistics, Regression Analysis, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      931 reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Building Statistical Models in R: Linear Regression

      Skills you'll gain: Exploratory Data Analysis, Statistical Modeling, Regression Analysis, Data Visualization, Data Analysis, Statistical Methods, Scatter Plots, R Programming, Plot (Graphics), Predictive Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • U

      University of Michigan

      Raising Capital: Credit Tech, Coin Offerings, and Crowdfunding

      Skills you'll gain: FinTech, Fundraising and Crowdsourcing, Mobile Banking, Banking, Fundraising, Capital Markets, Consumer Lending, Blockchain, Credit Risk, Financial Services, Lending and Underwriting, Financial Analysis, Commercial Lending

      4.7
      Rating, 4.7 out of 5 stars
      ·
      299 reviews

      Beginner · Course · 1 - 4 Weeks

    Logistic Regression learners also search

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    Predictive Modeling
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    1…121314…45

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

    • Introduction to Statistical Analysis: Hypothesis Testing: SAS
    • Practical Data Science with MATLAB: MathWorks
    • Launching into Machine Learning: Google Cloud
    • Bayesian Statistics: Techniques and Models: University of California, Santa Cruz
    • Market Research: Queen Mary University of London
    • Data Analysis and Interpretation: Wesleyan University
    • Accounting Data Analytics: University of Illinois Urbana-Champaign
    • Sports Performance Analytics: University of Michigan
    • Precalculus through Data and Modelling: Johns Hopkins University
    • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan 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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