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Coursera

Introduction to Linear Regression Training

via Coursera

Overview

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This foundational course on linear regression equips you with the essential knowledge and hands-on skills to build predictive models. Begin with core ML concepts and algorithms, then progress to simple and multiple linear regression techniques. Learn how regression is applied in real-world scenarios, including a detailed profit estimation case study, to strengthen both theory and practice for data-driven decision-making. No prior machine learning knowledge is required. By the end of this course, you will be able to: - Grasp ML Basics: Understand core machine learning concepts and algorithms - Master Regression: Differentiate between simple and multiple linear regression - Apply Techniques: Use regression models to solve real-world business problems - Interpret Insights: Analyze regression outcomes and extract actionable predictions - Build Confidence: Strengthen both theoretical knowledge and practical application Ideal for professionals seeking to develop strong foundations in machine learning and predictive analytics.

Syllabus

  • Foundations of Linear Regression
    • Master the foundations of linear regression in this beginner-friendly module. Start with an overview of machine learning and its core algorithms before diving into real-world applications of regression. Learn step-by-step concepts of simple and multiple linear regression, gain clarity through structured parts, and build the skills to apply regression models effectively in predictive analytics.
  • Applying Linear Regression
    • This module on applying linear regression helps you translate theory into practice with real-world business scenarios. Explore a detailed case study on profit estimation, broken into step-by-step parts to build hands-on experience in applying regression models. Conclude with key takeaways that reinforce concepts and equip you to leverage linear regression for accurate company profit predictions.

Taught by

Priyanka Mehta

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