SAS Statistics Foundations​ Learning Subscription

Applied Statistics for Machine Learning Associate Certification

• COURSE

  Statistics You Need to Know for Machine Learning

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  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.
  
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• CERTIFICATION PREP

  SAS Certified Associate: Applied Statistics for Machine Learning

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  As you prepare for the Applied Statistics for Machine Learning certification exam, you will develop a deep understanding of statistical and machine learning concepts as well as learn how to apply explanatory and predictive modeling techniques using SAS Viya.
  
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• CERTIFICATION PREP

  Practice Exam: Applied Statistics for Machine Learning

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  SAS Certified Specialist: Applied Statistics for Machine Learning
  
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SAS Statistical Business Analyst Certification

• COURSE

  Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression

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  This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression. This course (or equivalent knowledge) is a prerequisite to many of the courses in the statistical analysis curriculum.
  
  A more advanced treatment of ANOVA and regression occurs in the Statistics 2: ANOVA and Regression course. A more advanced treatment of logistic regression occurs in the Categorical Data Analysis Using Logistic Regression course and the Predictive Modeling Using Logistic Regression course.
  
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• COURSE

  Predictive Modeling Using Logistic Regression

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• CERTIFICATION PREP

  SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling

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  Preparation for the SAS Statistical Business Analysis Using SAS 9: Regression and Modeling certification exam involves learning how to conduct and interpret complex statistical data analysis. You will be guided into analyses of variance, linear and logistic regressions, preparing inputs for predictive models and measuring model performance.
  
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Principles and Best Practices

• COURSE

  Graphing Data Effectively and Avoiding Common Pitfalls

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• COURSE

  The Modeling Life Cycle for Data Scientists

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• COURSE

  Responsible Innovation and Trustworthy AI

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  This course is designed for anyone who wants to gain a deeper understanding about the importance of trust and responsibility in AI, analytics, and innovation. The content is especially geared to those who are making business decisions based on machine learning and AI systems and those who are designing and training AI systems.
  
  Whether you are a programmer, an executive, an advisory board member, a tester, a manager, or an individual contributor, this course helps you gain foundational knowledge and skills to consider the issues related to responsible innovation and trustworthy AI. Empowered with the knowledge from this course, you can strive to find ways to design, develop, and use machine learning and AI systems more responsibly.
  
  We expect that each module can be completed in under an hour, and you can work at your own pace to complete the material. As we release new modules, you might lose progress through the material that you have completed, so please make a note of where you are leaving off before exiting the course.
  
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• COURSE

  Modern Data Science with SAS® Viya® Workbench: Unified Development with SAS®, Python, and R

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