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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

      Introduction to Machine Learning: Supervised Learning

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Decision Tree Learning, Scikit Learn (Machine Learning Library), Matplotlib, Random Forest Algorithm, Machine Learning, Predictive Modeling, Data Science, Python Programming, Classification And Regression Tree (CART), Mathematical Modeling, Applied Mathematics, Exploratory Data Analysis, Statistical Programming, Regression Analysis, Feature Engineering, Data Cleansing, Performance Tuning

      Build toward a degree

      3.4
      Rating, 3.4 out of 5 stars
      ·
      75 reviews

      Intermediate · Course · 1 - 3 Months

    • C

      CertNexus

      CertNexus Certified Data Science Practitioner

      Skills you'll gain: Extract, Transform, Load, Data Analysis, Jupyter, Data Visualization, Unsupervised Learning, Applied Machine Learning, Statistical Analysis, Exploratory Data Analysis, Machine Learning, Analytical Skills, Data Manipulation, Data Cleansing, Data Processing, Stakeholder Engagement, Project Scoping, Data Presentation, Business Priorities, Classification And Regression Tree (CART), Stakeholder Management, Business Analytics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      70 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • C

      Coursera Project Network

      Diabetes Prediction With Pyspark MLLIB

      Skills you'll gain: Data Cleansing, Apache Spark, PySpark, Data Manipulation, Applied Machine Learning, Data Processing, Classification And Regression Tree (CART), Predictive Modeling, Regression Analysis, Machine Learning, Google Cloud Platform

      4.6
      Rating, 4.6 out of 5 stars
      ·
      22 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • N

      New York University

      Fundamentals of Machine Learning in Finance

      Skills you'll gain: Supervised Learning, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Machine Learning Algorithms, Decision Tree Learning, Machine Learning, Predictive Modeling, Financial Trading, Financial Market, Reinforcement Learning, Scikit Learn (Machine Learning Library), Correlation Analysis, Exploratory Data Analysis, Portfolio Management, Python Programming, Artificial Neural Networks, Jupyter

      3.7
      Rating, 3.7 out of 5 stars
      ·
      338 reviews

      Intermediate · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Employee Attrition Prediction Using Machine Learning

      Skills you'll gain: Data Visualization, Feature Engineering, Data Cleansing, Predictive Modeling, Scikit Learn (Machine Learning Library), Classification And Regression Tree (CART), Applied Machine Learning, Regression Analysis, Supervised Learning, Predictive Analytics, Machine Learning, Human Resources, Decision Tree Learning, Employee Retention

      4.4
      Rating, 4.4 out of 5 stars
      ·
      13 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • I

      IBM

      Deep Learning with PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Deep Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Applied Machine Learning, Supervised Learning, Regression Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      41 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      Machine Learning Capstone

      Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Data Analysis, Applied Machine Learning, Statistical Analysis, Data Presentation, Technical Communication, Machine Learning, Scikit Learn (Machine Learning Library), Python Programming, Tensorflow, Regression Analysis, Keras (Neural Network Library), Artificial Neural Networks

      4.6
      Rating, 4.6 out of 5 stars
      ·
      133 reviews

      Advanced · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Build and deploy a stroke prediction model using R

      Skills you'll gain: Feature Engineering, Predictive Modeling, Predictive Analytics, R Programming, Data Analysis, Statistical Modeling, Statistical Analysis, Data Cleansing, Exploratory Data Analysis, Applied Machine Learning, Data Manipulation, Application Deployment, Data Transformation, Machine Learning Methods, Interactive Data Visualization

      4.4
      Rating, 4.4 out of 5 stars
      ·
      17 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      U

      Universidade de São Paulo

      Econometria Básica Aplicada

      Skills you'll gain: Econometrics, Regression Analysis, Statistical Inference, Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, Economics, Mathematical Modeling, Time Series Analysis and Forecasting, Data Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      168 reviews

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Machine Learning with Spark on Google Cloud Dataproc

      Skills you'll gain: Apache Spark, Google Cloud Platform, Predictive Modeling, Big Data, Applied Machine Learning, Cloud Computing, Statistical Modeling

      Intermediate · Project · Less Than 2 Hours

    • I

      IIT Bombay

      Introduction to Internet of Things

      Skills you'll gain: Internet Of Things, Network Protocols, Wireless Networks, General Networking, Emerging Technologies, Data Analysis, Systems Design, Scikit Learn (Machine Learning Library), Regression Analysis, Pandas (Python Package), Unsupervised Learning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      54 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Data Science with R - Capstone Project

      Skills you'll gain: Shiny (R Package), Data Presentation, Exploratory Data Analysis, Data Wrangling, Predictive Modeling, Tidyverse (R Package), Data Science, Data Collection, Data Manipulation, Dashboard, Data Analysis, Data Cleansing, R Programming, Statistical Modeling, Regression Analysis, Ggplot2, Data Transformation, Web Scraping, SQL

      4.6
      Rating, 4.6 out of 5 stars
      ·
      91 reviews

      Intermediate · Course · 1 - 3 Months

    Logistic Regression learners also search

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    1…181920…44

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

    • Introduction to Machine Learning: Supervised Learning: University of Colorado Boulder
    • CertNexus Certified Data Science Practitioner: CertNexus
    • Diabetes Prediction With Pyspark MLLIB: Coursera Project Network
    • Fundamentals of Machine Learning in Finance: New York University
    • Employee Attrition Prediction Using Machine Learning: Coursera Project Network
    • Deep Learning with PyTorch: IBM
    • Machine Learning Capstone: IBM
    • Build and deploy a stroke prediction model using R: Coursera Project Network
    • Econometria Básica Aplicada: Universidade de São Paulo
    • Machine Learning with Spark on Google Cloud Dataproc: Google Cloud

    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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