Fundamentals of Regression Analysis

  • BeginnerLevel

  • 1 hrs 30 minsDuration

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About this Course

  • Learn the fundamentals, types, applications, key assumptions, advantages, and limitations of regression analysis.
  • Covers Linear, Logistic, Ridge, Lasso, Polynomial, Stepwise, and other advanced regression techniques.
  • Hands-on coding in Python with real-world use cases and model selection strategies.

Learning Outcomes

Understaning Regression

Learn the basics, types, and applications of regression analysis.

Regression Techniques

Gain expertise in Linear, Logistic, Ridge, and Lasso regression.

Develop Practical Skills

Implement regression models using Python for real-world scenarios.

Selection & Evaluation

Learn to choose the right regression model and handle challenges.

Meet the instructor

Our instructor and mentors carry years of experience in data industry

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Kunal Jain

Founder & CEO, Analytics Vidhya

Kunal has 15+ years of experience in the field of Data Science and is the founder and CEO of Analytics Vidhya- the world's 2nd largest Data Science community.

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With this course you’ll get

  • 120 hour

    Duration

  • Kunal Jain

    Instructor

  • Beginner

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Globally recognized certificate
  • Verifiable online credential
  • Enhances professional credibility

Frequently Asked Questions

Looking for answers to other questions?

Regression analysis is a statistical technique used to identify relationships between a dependent variable and one or more independent variables.

Common types include Linear Regression, Logistic Regression, Ridge Regression, Lasso Regression, and Polynomial Regression.

Ridge adds a squared penalty to the loss function, while Lasso adds an absolute penalty, which can shrink some coefficients to zero.

Regression can be implemented in Python, R, Excel, Minitab, and KNIME, but Python is widely used in data science.

Yes, you will receive a certificate of completion after successfully finishing the course and assessments.

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