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Part of the Master of Science in Data Science degree

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Regression and Classification

University of Colorado Boulder

About this Course

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Introduction to Statistical Learning will explore concepts in statistical modeling, such as when to use certain models, how to tune those models, and if other options will provide certain trade-offs. We will cover Regression, Classification, Trees, Resampling, Unsupervised techniques, and much more!
This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Photo by Nicholas Cappello on Unsplash

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Intermediate Level

Intro Statistics and Foundational Math

Approx. 35 hours to complete

English

Subtitles: English

What you will learn

Express why Statistical Learning is important and how it can be used.

Identify the strengths, weaknesses and caveats of different models and choose the most appropriate model for a given statistical problem.

Determine what type of data and problems require supervised vs. unsupervised techniques.

Skills you will gain

Statistics
Data Science
R Programming

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Intermediate Level

Intro Statistics and Foundational Math

Approx. 35 hours to complete

English

Subtitles: English

Instructor

James Bird

Instructor

Data Science & Applied Mathematics

1,245 Learners

3 Courses

Offered by

University of Colorado Boulder

CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Data Science from University of Colorado Boulder. If you are admitted to the full program, your courses count towards your degree learning.

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Syllabus - What you will learn from this course

Week

Week 1

1 hour to complete

Statistical Learning Introduction

Introduction to overarching and foundational concepts in Statistical Learning.

1 hour to complete

9 videos (Total 37 min), 1 reading

Week

Week 2

7 hours to complete

Accuracy

Exploration into assessing models in different situations. How do we define a "best" model for given data?

7 hours to complete

6 videos (Total 34 min)

Week

Week 3

1 hour to complete

Simple Linear Regression

Introduction to Simple Linear Regression, such as when and how to use it.

1 hour to complete

5 videos (Total 30 min)

Week

Week 4

10 hours to complete

Multiple Linear Regression

A deep dive into multiple linear regression, a strong and extremely popular technique for a continuous target.

10 hours to complete

6 videos (Total 35 min)

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

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Regression and Classification

Regression and Classification