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Linear Regression Courses

Linear regression courses can help you learn how to analyze relationships between variables, interpret coefficients, and evaluate model performance. You can build skills in data visualization, hypothesis testing, and making predictions based on data trends. Many courses introduce tools like Python, R, and Excel, that support implementing regression models and analyzing datasets effectively.


Popular Linear Regression Courses and Certifications


  • Status: Free Trial
    Free Trial
    R

    Rice University

    Linear Regression for Business Statistics

    Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Regression Analysis, Statistical Analysis, Statistical Modeling, Statistical Inference, Business Analytics, Microsoft Excel, Model Evaluation, Estimation, Data Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1.4K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Pennsylvania

    Business and Financial Modeling

    Skills you'll gain: Risk Management, Business Modeling, Mathematical Modeling, Data-Driven Decision-Making, Portfolio Management, Forecasting, Regression Analysis, Financial Modeling, Statistical Modeling, Risk Analysis, Predictive Modeling, Presentations, Spreadsheet Software, Microsoft PowerPoint, Investment Management, Financial Statements, Data Modeling, Quantitative Research, Business Analytics, Microsoft Excel

    4.5
    Rating, 4.5 out of 5 stars
    ·
    11K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Advanced Excel Analytics, Automation & Data Analysis

    Skills you'll gain: Excel Macros, Data Validation, Scatter Plots, Pivot Tables And Charts, Microsoft Excel, Data Visualization, Regression Analysis, Excel Formulas, Histogram, Data Analysis, Data Integrity, Descriptive Statistics, Data Visualization Software, Spreadsheet Software, Analytics, Statistical Analysis, Data Analysis Expressions (DAX), Statistical Methods, Descriptive Analytics, Automation

    Beginner · Specialization · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Advanced SAS Programming, Macros & Reporting

    Skills you'll gain: Sampling (Statistics), Logistic Regression, SAS (Software), Predictive Analytics, Automation, Data Integration, Advanced Analytics, Debugging, Statistical Programming, SQL, Statistical Methods, Report Writing, Data Manipulation, Data Analysis, Model Evaluation, Statistical Reporting, Data Access, Microsoft Excel, Analysis, Finance

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Pennsylvania

    Finance & Quantitative Modeling for Analysts

    Skills you'll gain: Financial Reporting, Return On Investment, Financial Acumen, Financial Data, Capital Budgeting, Financial Statements, Business Modeling, Mathematical Modeling, Finance, Regression Analysis, Financial Modeling, Statistical Modeling, Income Statement, Risk Analysis, Financial Analysis, Spreadsheet Software, Capital Expenditure, Excel Formulas, Microsoft Excel, Corporate Finance

    4.5
    Rating, 4.5 out of 5 stars
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    17K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Introduction to Computer Vision

    Skills you'll gain: Image Analysis, Computer Vision, Deep Learning, Convolutional Neural Networks, Computer Graphics, Machine Learning Methods, Artificial Intelligence, Data Ethics, Microsoft Excel, Generative AI, Linear Algebra, Feature Engineering, Digital Signal Processing

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    23 reviews

    Beginner · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Everyday Excel

    Skills you'll gain: Microsoft Excel, Excel Formulas, Regression Analysis, Data Validation, Pivot Tables And Charts, Spreadsheet Software, Data Management, Data Visualization Software, Data Entry, Statistical Modeling, Data Cleansing, Financial Analysis, Predictive Modeling, Financial Modeling, Data Analysis Expressions (DAX), Data Import/Export, Analysis, Mathematical Modeling, Complex Problem Solving, Problem Solving

    4.7
    Rating, 4.7 out of 5 stars
    ·
    4.1K reviews

    Beginner · Specialization · 3 - 6 Months

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • Status: Free Trial
    Free Trial
    M

    Macquarie University

    Excel Skills for Business Forecasting

    Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, Model Evaluation, Regression Analysis, Microsoft Excel, Excel Formulas, Trend Analysis, Case Studies, Business Mathematics, Business Metrics, Predictive Modeling, Data Presentation, Statistical Visualization, Graphing, Business Economics, Statistical Modeling, Business Analytics, Decision Making, Process Optimization, Statistical Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    319 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    R

    Rice University

    Business Statistics and Analysis

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

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

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Analyze and Interpret Data Using Excel

    Skills you'll gain: Scatter Plots, Data Visualization, Regression Analysis, Excel Formulas, Microsoft Excel, Data Analysis, Descriptive Statistics, Data Visualization Software, Analytics, Statistical Analysis, Statistical Methods, Descriptive Analytics, Correlation Analysis, Statistics, Analysis, Exploratory Data Analysis, Pivot Tables And Charts, Trend Analysis

    Beginner · Course · 1 - 4 Weeks

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

    Coursera

    AI-Powered Business Analysis: Excel, KPIs & GenAI

    Skills you'll gain: Excel Macros, Key Performance Indicators (KPIs), Prompt Engineering, Data Storytelling, Performance Measurement, Regression Analysis, Business Metrics, Continuous Improvement Process, Performance Analysis, Business Process Improvement, Performance Improvement, Statistical Hypothesis Testing, Responsible AI, ChatGPT, Microsoft Excel, Generative AI, Data Visualization, Business Analysis, Statistical Analysis, Business Intelligence

    4.5
    Rating, 4.5 out of 5 stars
    ·
    406 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    M

    Macquarie University

    Statistics and Data Analysis with Excel

    Skills you'll gain: Pivot Tables And Charts, Sample Size Determination, Data Visualization, Statistical Inference, Data Visualization Software, Statistical Hypothesis Testing, Statistics, Data-Driven Decision-Making, Microsoft Excel, Correlation Analysis, Descriptive Statistics, Probability & Statistics, Data Analysis, Forecasting, Regression Analysis, Business Analytics, Spreadsheet Software, Statistical Modeling, Statistical Visualization, Data Presentation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    79 reviews

    Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

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

  • Linear Regression for Business Statistics: Rice University
  • Business and Financial Modeling: University of Pennsylvania
  • Advanced Excel Analytics, Automation & Data Analysis: EDUCBA
  • Advanced SAS Programming, Macros & Reporting: EDUCBA
  • Finance & Quantitative Modeling for Analysts: University of Pennsylvania
  • Introduction to Computer Vision: University of Colorado Boulder
  • Everyday Excel: University of Colorado Boulder
  • Excel Skills for Business Forecasting: Macquarie University
  • Business Statistics and Analysis: Rice University
  • Analyze and Interpret Data Using Excel: EDUCBA

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 statistical method used to model the relationship between a dependent variable and one or more independent variables. It is important because it provides a simple yet powerful way to predict outcomes and understand relationships in data. By fitting a linear equation to observed data, linear regression helps in making informed decisions based on trends and patterns. This technique is widely used in various fields, including economics, biology, engineering, and social sciences, making it a fundamental tool for data analysis.‎

A variety of job roles utilize linear regression skills, particularly in data-driven industries. Positions such as data analyst, statistician, business analyst, and data scientist often require proficiency in linear regression. Additionally, roles in marketing analytics, financial analysis, and healthcare analytics also benefit from this skill set. Understanding linear regression can enhance your ability to interpret data and make data-informed decisions, which is increasingly valuable in today's job market.‎

To effectively learn linear regression, you should focus on developing a solid foundation in statistics and mathematics, particularly in concepts like correlation, variance, and hypothesis testing. Familiarity with programming languages such as Python or R can also be beneficial, as these tools are commonly used for implementing linear regression models. Additionally, understanding data visualization techniques will help you interpret and present your findings clearly. Practical experience through projects or case studies can further reinforce your learning.‎

There are several excellent online courses available for learning linear regression. For a comprehensive introduction, consider Introduction to Linear Regression Training. If you're interested in applying linear regression in a business context, Linear Regression for Business Statistics is a great option. For those looking to explore more advanced applications, Generalized Linear Models and Nonparametric Regression offers deeper insights into the topic.‎

Yes. You can start learning linear regression on Coursera for free in two ways:

  1. Preview the first module of many linear regression courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in linear regression, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn linear regression, start by selecting a course that matches your current knowledge level and learning goals. Engage with the course materials, including video lectures and readings, and practice by working on exercises and projects. Utilize programming tools like Python or R to implement linear regression models on real datasets. Additionally, participate in online forums or study groups to discuss concepts and share insights with peers, which can enhance your understanding and retention.‎

Typical topics covered in linear regression courses include the fundamentals of regression analysis, the assumptions underlying linear regression models, methods for estimating parameters, and techniques for evaluating model performance. Courses often explore both simple and multiple linear regression, as well as applications in various fields. You may also learn about advanced topics such as regularization techniques and how to handle multicollinearity in datasets.‎

For training and upskilling employees, courses like Linear Regression and Modeling and Linear Regression Modeling for Health Data can be particularly beneficial. These courses provide practical applications of linear regression in different contexts, helping employees apply their learning directly to their work. Additionally, Linear Regression & Supervised Learning in Python offers a hands-on approach that can enhance skills relevant to data analysis roles.‎

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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