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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

    • N

      New York University

      Machine Learning and Reinforcement Learning in Finance

      Skills you'll gain: Supervised Learning, Reinforcement Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Artificial Neural Networks, Decision Tree Learning, Predictive Modeling, Financial Trading, Financial Market, Derivatives, Scikit Learn (Machine Learning Library), Markov Model, Regression Analysis, Deep Learning, Market Liquidity, Financial Services

      3.7
      Rating, 3.7 out of 5 stars
      ·
      814 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Prediction Models with Sports Data

      Skills you'll gain: Forecasting, Data Processing, Predictive Analytics, Predictive Modeling, Data Analysis, Market Data, Performance Analysis, Analytics, Regression Analysis, Probability & Statistics, Data Manipulation, Probability, Ethical Standards And Conduct

      4.5
      Rating, 4.5 out of 5 stars
      ·
      39 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Washington

      Practical Predictive Analytics: Models and Methods

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Statistical Machine Learning, Predictive Analytics, Advanced Analytics, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Big Data

      4.1
      Rating, 4.1 out of 5 stars
      ·
      320 reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Minnesota

      Optimization for Decision Making

      Skills you'll gain: Operations Research, Mathematical Modeling, Business Modeling, Business Analytics, Analytics, Data Modeling, Business Mathematics, Process Optimization, Data-Driven Decision-Making, Business Intelligence, Microsoft Excel, Solution Design, Decision Making, Linear Algebra, Resource Allocation, Graphing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      73 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Virginia

      Cost and Economics in Pricing Strategy

      Skills you'll gain: Price Negotiation, Market Dynamics, Product Strategy, Revenue Management, Cost Accounting, Economics, Demand Planning, Cost Benefit Analysis, Consumer Behaviour, Marketing Channel, Customer Analysis, Regression Analysis, Competitive Analysis, Statistical Methods

      4.8
      Rating, 4.8 out of 5 stars
      ·
      671 reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      Packt

      The STATA OMNIBUS: Regression and Modelling with STATA

      Skills you'll gain: Stata, Regression Analysis, Statistical Modeling, Statistical Analysis, Advanced Analytics, Correlation Analysis, Statistical Visualization, Data Manipulation, Sampling (Statistics), Statistical Hypothesis Testing, Descriptive Statistics

      Beginner · Course · 3 - 6 Months

    • K

      Kennesaw State University

      Six Sigma Advanced Define and Measure Phases

      Skills you'll gain: Process Capability, Team Management, Statistical Process Controls, Exploratory Data Analysis, Six Sigma Methodology, Probability & Statistics, Process Analysis, Statistical Analysis, Lean Six Sigma, Process Mapping, Correlation Analysis, Data Analysis, Data Collection, Regression Analysis, Process Improvement, Quality Improvement, Business Process, Graphing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 3 Months

    • A

      Arizona State University

      Design of Experiments

      Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Regression Analysis, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Design Strategies, Probability & Statistics, Data Analysis, Mathematical Modeling, Data Transformation, Descriptive Statistics, Probability Distribution, Statistical Hypothesis Testing, Variance Analysis, Quality Control

      4.7
      Rating, 4.7 out of 5 stars
      ·
      359 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California San Diego

      Python Data Products for Predictive Analytics

      Skills you'll gain: Supervised Learning, Feature Engineering, Predictive Modeling, Data Processing, Data Manipulation, Applied Machine Learning, Interactive Data Visualization, Design Thinking, Advanced Analytics, Web Scraping, Machine Learning Algorithms, Flask (Web Framework), Data Visualization Software, Scikit Learn (Machine Learning Library), Application Deployment, Data Science, Data Validation, Verification And Validation, Django (Web Framework), Regression Analysis

      4.2
      Rating, 4.2 out of 5 stars
      ·
      245 reviews

      Intermediate · Specialization · 3 - 6 Months

    • 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

    • U

      University of Illinois Urbana-Champaign

      Text Mining and Analytics

      Skills you'll gain: Text Mining, Data Mining, Unstructured Data, Statistical Analysis, Natural Language Processing, Analytics, Data Analysis, Unsupervised Learning, Probability & Statistics, Regression Analysis, Predictive Modeling, Supervised Learning, Machine Learning Algorithms

      4.5
      Rating, 4.5 out of 5 stars
      ·
      734 reviews

      Mixed · 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

    Logistic Regression learners also search

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    1…111213…44

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

    • Machine Learning and Reinforcement Learning in Finance: New York University
    • Prediction Models with Sports Data: University of Michigan
    • Practical Predictive Analytics: Models and Methods: University of Washington
    • Optimization for Decision Making: University of Minnesota
    • Cost and Economics in Pricing Strategy: University of Virginia
    • The STATA OMNIBUS: Regression and Modelling with STATA: Packt
    • Six Sigma Advanced Define and Measure Phases: Kennesaw State University
    • Design of Experiments: Arizona State University
    • Python Data Products for Predictive Analytics: University of California San Diego
    • Introduction to Statistical Analysis: Hypothesis Testing: SAS

    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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