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Regression and Classification
Master statistical learning techniques for data analysis with hands-on practice in R. From linear regression to classification models.
Course Cost
Free course
Intermediate
Skill Level
33 Hours
Self-paced lessons
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Statistical Learning for Data Science Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
2,437 Enrolled
English
What you'll learn
Master statistical learning fundamentals and their applications
Develop skills in supervised and unsupervised learning techniques
Gain proficiency in regression and classification methods
Learn to assess and select appropriate models
Understand the bias-variance trade-off in statistical learning
Apply statistical learning techniques using R programming
Skills you'll gain
This course includes:
3.8 Hours PreRecorded video
2 programming assignments, 1 discussion prompt
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This comprehensive course explores statistical learning concepts essential for data science and machine learning. Beginning with foundational principles of supervised and unsupervised learning, students progress through regression techniques, classification methods, and model assessment. The curriculum emphasizes both theoretical understanding and practical application, featuring hands-on programming assignments in R. Topics include linear regression, logistic regression, LDA, QDA, and model selection techniques.
Statistical Learning Introduction
Module 1 · 1 Hours to complete
Accuracy
Module 2 · 6 Hours to complete
Simple Linear Regression
Module 3 · 40 Minutes to complete
Multiple Linear Regression
Module 4 · 9 Hours to complete
Classification Overview
Module 5 · 51 Minutes to complete
Classification Models
Module 6 · 15 Hours to complete
Fee Structure
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Students
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Frequently asked Questions
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