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Statistics You Need to Know for Machine Learning
VST1 : VST141
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 "bigness" 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 using SAS Viya. Knowledge of statistics relevant to machine learning will prepare you to become a data scientist. The course prepares you for future instruction on doing machine learning (including its underlying methodology that has statistical foundations) and enables you to develop a deeper understanding of machine learning models.
This course is a prerequisite to many of the courses in the data science curriculum. A more advanced treatment of machine learning occurs in the courses Machine Learning Using SAS Viya, Interactive Machine Learning in SAS Viya, SAS Visual Statistics in SAS Viya: Interactive Model Building, and Supervised Machine Learning Procedures Using SAS Viya in SAS Studio.
For students interested in statistics for inference and explanatory analysis used in scientific and medical research, Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression is an appropriate foundational course.
This course is a prerequisite to many of the courses in the data science curriculum. A more advanced treatment of machine learning occurs in the courses Machine Learning Using SAS Viya, Interactive Machine Learning in SAS Viya, SAS Visual Statistics in SAS Viya: Interactive Model Building, and Supervised Machine Learning Procedures Using SAS Viya in SAS Studio.
For students interested in statistics for inference and explanatory analysis used in scientific and medical research, Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression is an appropriate foundational course.
Learn How To
- Explain the relevance of statistics in big data and machine learning.
- Relate statistical and data science terminology.
- Generate descriptive statistics and explore data with graphs.
- Detect associations among variables.
- Perform linear regression for explanatory modeling.
- Compare explanatory modeling with predictive modeling.
- Describe the trade-off between bias and variance.
- Fit a logistic regression model for predictive modeling.
- Score new data.
- Explain the statistical foundations of machine learning.
- Discuss data difficulties and modeling issues and their statistical solutions.
Who Should Attend
Anyone in the field of data science who does not yet have a deep understanding of statistical and machine learning concepts or wants to enhance their knowledge, which might include business analysts, data analysts, marketing analysts, marketing managers, data scientists, data engineers, financial analysts, data miners, statisticians, mathematicians, and others who work in allied areas
Prerequisites
Before attending this course, you should have experience using computer software. It is beneficial if you have completed the equivalent of an undergraduate course in statistics covering distribution of data, p-values, hypothesis testing, and regression. No prior SAS experience is needed.
SAS Products Covered
SAS Viya
Course Outline
Statistics and Machine Learning
- Relevance of statistics in big data and machine learning.
- Terminology and vocabulary.
- Introduction to SAS Viya and SAS Studio.
- Introduction to statistical analysis.
- Descriptive statistics.
- Inferential statistics.
- Correlation and simple linear regression.
- Multiple regression and model selection.
- Model diagnostics.
- Introduction to predictive modeling.
- Categorical associations.
- Logistic regression model.
- Model deployment.
- Overview of machine learning.
- Data pre-processing for machine learning models.
- Model evaluation, estimation, and post-training tasks.
Live Class Schedule
Duration: 21 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
Live Class Schedule
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| 01-03,06-08 OCT 2025 | Live Web, US | 1:00 PM-4:30 PM EDT | English | 2,400 USD | |
| 03-05,08-10 DEC 2025 | Live Web, US | 1:00 PM-4:30 PM EST | English | 2,400 USD | |
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.
This course helps prepare you to earn the following SAS Credentials:
SAS Certification Manager
SAS partners with Pearson VUE to provide you with the best possible certification experience.
Certification Resources
