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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 Washington

      Machine Learning: Classification

      Skills you'll gain: Classification And Regression Tree (CART), Applied Machine Learning, Supervised Learning, Predictive Modeling, Text Mining, Machine Learning Algorithms, Data Cleansing, Scalability, Machine Learning, Natural Language Processing, Big Data, Probability & Statistics, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Mixed · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Business Analytics with Excel: Elementary to Advanced

      Skills you'll gain: Risk Modeling, Operations Research, Regression Analysis, Microsoft Excel, Business Analytics, Risk Analysis, Business Process Modeling, Business Modeling, Data Modeling, Resource Allocation, Statistical Analysis, Process Optimization, Financial Analysis, Predictive Analytics, Transportation Operations, Complex Problem Solving, Linear Algebra

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.8K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      M

      Macquarie University

      Excel Skills for Statistics and Data Analysis: Intermediate

      Skills you'll gain: Interactive Data Visualization, Pivot Tables And Charts, Statistical Inference, Microsoft Excel, Correlation Analysis, Statistics, Statistical Hypothesis Testing, Probability & Statistics, Statistical Analysis, Regression Analysis, Data Analysis, Sampling (Statistics), Descriptive Statistics, Forecasting

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      P

      Packt

      Foundations of ML & Python for Data Science

      Skills you'll gain: Data Manipulation, Python Programming, Probability & Statistics, Pandas (Python Package), Data Science, Statistical Analysis, NumPy, Applied Machine Learning, Machine Learning, Machine Learning Algorithms, Descriptive Statistics, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Probability

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      P

      Packt

      Advanced ML Algorithms & Unsupervised Learning

      Skills you'll gain: Dimensionality Reduction, Unsupervised Learning, Deep Learning, Random Forest Algorithm, Machine Learning Algorithms, Machine Learning, Decision Tree Learning, Classification And Regression Tree (CART), Feature Engineering, Supervised Learning, Statistical Machine Learning, Predictive Modeling, Artificial Intelligence, Exploratory Data Analysis

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Linear Regression and Modeling

      Skills you'll gain: Regression Analysis, Data Analysis Software, Statistical Analysis, R Programming, Statistical Modeling, Statistical Inference, Correlation Analysis, Statistical Methods, Exploratory Data Analysis, Mathematical Modeling, Predictive Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Comparative Effectiveness and Real-World Evidence

      Skills you'll gain: Clinical Research, Pharmaceuticals, Clinical Trials, Pharmacology, Research Design, Health Policy, Epidemiology, Research Methodologies, Research, Statistical Methods, Real Time Data, Statistical Analysis, Regression Analysis

      Mixed · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      I

      Illinois Tech

      Introduction to Data Science Techniques

      Skills you'll gain: Time Series Analysis and Forecasting, Statistical Analysis, Data Analysis, Machine Learning Algorithms, Data Visualization, Data Science, Exploratory Data Analysis, Data Presentation, Statistical Programming, Statistical Methods, Statistical Machine Learning, Statistical Reporting, Data Cleansing, Forecasting, Applied Machine Learning, Analytics, Regression Analysis, R Programming, Machine Learning, Statistical Modeling

      Build toward a degree

      4.2
      Rating, 4.2 out of 5 stars
      ·
      14 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      C

      Case Western Reserve University

      Practical Geospatial Geostatistical Modeling

      Skills you'll gain: Geostatistics, Exploratory Data Analysis, Spatial Data Analysis, Spatial Analysis, Geospatial Mapping, Geospatial Information and Technology, Descriptive Statistics, Box Plots, Statistical Methods, Statistical Modeling, R Programming, Plot (Graphics), Statistical Analysis, Rmarkdown, Probability & Statistics, Data Cleansing, Data Analysis, Regression Analysis, Correlation Analysis, Data Validation

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis with Python

      Skills you'll gain: Predictive Modeling, Exploratory Data Analysis, Data Wrangling, Data Analysis, Data Import/Export, Pandas (Python Package), Statistical Modeling, Data-Driven Decision-Making, Data Manipulation, Scikit Learn (Machine Learning Library), Regression Analysis, Feature Engineering, Matplotlib, Data Cleansing, NumPy, Descriptive Statistics, Supervised Learning, Data Pipelines

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Meta

      Statistics Foundations

      Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Data Modeling, Statistics, Probability & Statistics, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Quantitative Research, Analytics, Descriptive Analytics, Time Series Analysis and Forecasting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      335 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rutgers the State University of New Jersey

      Supply Chain Management

      Skills you'll gain: Strategic Sourcing, Lean Six Sigma, Lean Manufacturing, Demand Planning, Procurement, Supplier Relationship Management, Forecasting, Process Improvement, Supplier Management, Operations Management, Customer Demand Planning, Purchasing, Production Process, Supply Management, Operational Efficiency, Warehouse Management, Supply Chain Planning, Inventory and Warehousing, Inventory Management System, Transportation, Supply Chain, and Logistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    Logistic Regression learners also search

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    1234…45

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

    • Machine Learning: Classification: University of Washington
    • Business Analytics with Excel: Elementary to Advanced: Johns Hopkins University
    • Excel Skills for Statistics and Data Analysis: Intermediate: Macquarie University
    • Foundations of ML & Python for Data Science: Packt
    • Advanced ML Algorithms & Unsupervised Learning: Packt
    • Linear Regression and Modeling : Duke University
    • Comparative Effectiveness and Real-World Evidence: Johns Hopkins University
    • Introduction to Data Science Techniques: Illinois Tech
    • Practical Geospatial Geostatistical Modeling: Case Western Reserve University
    • Data Analysis with Python: IBM

    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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