When it comes to using data, there are two main camps, traditional statistics and machine learning, and the two camps complement each other. Statistics remains highly relevant, irrespective of the size of data. Its role remains what it has always been, but it is even more important now. There is a need to transition from traditional statistical modeling to the machine learning world. This course introduces the statistical background necessary for machine learning. Knowledge of statistics relevant to machine learning will prepare you to become a data scientist. The course prepares you for future instruction on machine learning (including its underlying methodology that has statistical foundations) and enables you to develop a deeper understanding of machine learning models.

Statistics You Need to Know for Machine Learning

Statistics You Need to Know for Machine Learning
This course is part of SAS Machine Learning Engineer Professional Certificate

Instructor: Catherine Truxillo
Access provided by EDGE Group
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
5 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Explain the relevance of statistics in machine learning.
Perform linear and logistic regression with practical troubleshooting tips.
Details to know

Shareable certificate
Add to your LinkedIn profile
Assessments
71 assignments
Taught in English
Recently updated!
December 2025
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Build your Probability and Statistics expertise
This course is part of the SAS Machine Learning Engineer Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from SAS

There are 5 modules in this course
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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