Complete SAS Guide - Learn SAS and Become a Data Ninja

Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course is designed to transform you from a beginner to a proficient SAS programmer, covering a wide range of topics essential for effective data management and analysis. You will start by setting up your SAS environment and navigating through common installation and data upload challenges. As you progress, you will delve into the fundamentals of data importing and explore various file formats including .txt, .csv, and .xlsx. This foundational knowledge will pave the way for mastering SAS syntax and understanding the nuances of data and proc steps. Moving forward, you will explore data manipulation techniques that are crucial for real-world applications. The course provides an in-depth understanding of creating and managing variables, filtering observations, and using decision-making and looping structures. By comparing SAS with R and Python, you will gain a broader perspective on data handling and analysis. You will also learn to utilize SAS functions for data cleaning and manipulation, making complex tasks like handling large datasets and dealing with missing data more efficient and manageable. In the final sections, you will tackle advanced topics such as statistical analysis, predictive modeling, and SAS SQL. Through practical examples and case studies, you will learn to apply statistical tests, perform regression analysis, and construct predictive models. The course concludes with a thorough understanding of macro programming and predictive modeling techniques, equipping you with the skills to tackle sophisticated data problems in professional settings. This course is ideal for data analysts, statisticians, and professionals in fields such as finance, healthcare, and business analytics who want to leverage SAS for data management and analysis. Prior experience with programming is helpful but not required, as the course starts with the basics and progresses to advanced topics.