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    • Linear Regression

    Linear Regression Courses Online

    Explore linear regression for statistical modeling. Learn to analyze relationships between variables and make predictions based on data.

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    Explore the Linear Regression Course Catalog

    • K

      Kennesaw State University

      Six Sigma Yellow Belt

      Skills you'll gain: Six Sigma Methodology, Root Cause Analysis, Lean Methodologies, Data Collection, Process Improvement, Quality Improvement, Process Optimization, Lean Six Sigma, Correlation Analysis, Statistical Hypothesis Testing, Kaizen Methodology, Process Analysis, Probability Distribution, Regression Analysis, Process Capability, Business Process, Statistical Process Controls, Quality Management, Team Management, Continuous Improvement Process

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Toronto

      Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Control Systems, Embedded Software, Automation, Deep Learning, Software Architecture, Simulations, Safety Assurance, Artificial Neural Networks, Global Positioning Systems, Hardware Architecture, Systems Architecture, Artificial Intelligence, Estimation, Algorithms, Machine Learning Methods, Predictive Modeling, Scenario Testing, Spatial Data Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • I

      IBM

      Introduction to Neural Networks and PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Deep Learning, Predictive Modeling, Probability & Statistics, Machine Learning, Regression Analysis, Data Manipulation, Linear Algebra

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Natural Language Processing

      Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Algorithms, Keras (Neural Network Library), Linear Algebra, Data Cleansing, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Algebra: Elementary to Advanced

      Skills you'll gain: Algebra, Mathematical Modeling, Graphing, Arithmetic, Advanced Mathematics, Applied Mathematics, General Mathematics, Mathematical Theory & Analysis, Analytical Skills, Probability & Statistics, Geometry

      4.8
      Rating, 4.8 out of 5 stars
      ·
      723 reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Data Analysis with Python

      Skills you'll gain: Data Wrangling, Data Cleansing, Data Analysis, Data Manipulation, Data Import/Export, Exploratory Data Analysis, Data Science, Statistical Analysis, Descriptive Statistics, Regression Analysis, Predictive Modeling, Pandas (Python Package), Scikit Learn (Machine Learning Library), Machine Learning Methods, Data Pipelines, NumPy

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

      Intermediate · Course · 1 - 3 Months

    • D

      Duke University

      AI Product Management

      Skills you'll gain: Deep Learning, MLOps (Machine Learning Operations), Data Ethics, Data Management, Unsupervised Learning, Human Computer Interaction, User Experience Design, Classification And Regression Tree (CART), Data Quality, Human Centered Design, Machine Learning, Human Factors, Regression Analysis, Technical Management, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Artificial Neural Networks, Decision Tree Learning, Data Processing, Personally Identifiable Information

      4.7
      Rating, 4.7 out of 5 stars
      ·
      777 reviews

      Beginner · Specialization · 3 - 6 Months

    • R

      Rice University

      Business Statistics and Analysis

      Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Analysis, Statistical Modeling, Excel Formulas, Data Analysis, Data Presentation, Statistics, Business Analysis, Statistical Methods, Sample Size Determination, Statistical Inference

      4.7
      Rating, 4.7 out of 5 stars
      ·
      13K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Machine Learning with Python

      Skills you'll gain: Supervised Learning, Feature Engineering, Jupyter, Unsupervised Learning, Scikit Learn (Machine Learning Library), Python Programming, Predictive Modeling, Machine Learning, Dimensionality Reduction, Classification And Regression Tree (CART), Matplotlib, NumPy, Regression Analysis, Statistical Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      17K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • J

      Johns Hopkins University

      Data Science: Statistics and Machine Learning

      Skills you'll gain: Shiny (R Package), Rmarkdown, Regression Analysis, Leaflet (Software), Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Data Visualization, Statistical Machine Learning, Feature Engineering, Statistical Analysis, Statistical Modeling, Probability, Data Science, Data Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7.2K reviews

      Intermediate · Specialization · 3 - 6 Months

    Linear Regression learners also search

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    1…456…73

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

    • Six Sigma Yellow Belt: Kennesaw State University
    • Self-Driving Cars: University of Toronto
    • Introduction to Neural Networks and PyTorch: IBM
    • Natural Language Processing: DeepLearning.AI
    • Algebra: Elementary to Advanced: Johns Hopkins University
    • Data Analysis with Python: IBM
    • AI Product Management: Duke University
    • Business Statistics and Analysis: Rice University
    • Reinforcement Learning: University of Alberta
    • Machine Learning 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 Linear Regression

    Linear regression is a type of statistical data analysis that examines which variables help significantly predict the outcome of a situation. You can use linear regression to determine the relationships between one dependent variable and one or more independent variables to sort out which variables will contribute most to the outcome you seek to achieve. Linear regression also helps you forecast the impact that changes to variables will make in different scenarios. It's a tool you can use to help predict outcomes and make adjustments to help achieve the outcome you're looking for.‎

    If you're in a career that relies on data analysis, linear regression is a tool that can help you determine the relationship between variables that affect scenarios that you need to predict or plan for. You can use linear regression to anticipate how the factors that affect a situation now will make a difference in the future. For example, you can use linear regression to predict the cost of a project or the amount of time it will take to complete the project based on different variables. Linear regression can help you make more informed and educated decisions to better navigate the present and plan for the future.‎

    Data analysts use linear regression in different areas of business to determine which variables affect outcomes the most. You can apply linear regression as a data scientist or analyst with a single company or in a consultant role across multiple businesses. You can even set up your own business as a consultant to be in control of your own schedule and career trajectory. Analysts use linear regression in polling and surveys as well as in policy research fields, and various corporations use data analysis to help plan for the future. You can also apply your knowledge of linear regression in higher education and as a professor or research assistant.‎

    You can use online courses to learn linear regression in order to deepen your knowledge and skills in your current job or to find a new career. Whether you're already familiar with linear regression or whether you're brand new to the concept, online courses can give you the knowledge you need to apply linear regression in your workplace. Online courses not only teach you the concepts, but they also provide you with real-life applications of what you're learning. One of the biggest benefits of online learning is that you can sharpen your skills in a way that fits your schedule and lifestyle. You can walk away from your online learning confident in what you've discovered about linear regression and prepared to apply it to your career.‎

    Online Linear Regression courses offer a convenient and flexible way to enhance your knowledge or learn new Linear Regression skills. Choose from a wide range of Linear Regression courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Linear 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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