Getting Started with SAS Programming
Learn SAS programming for data science, machine learning, and AI. Access, explore, prepare, and analyze data using SAS Studio. Gain essential skills in data validation, manipulation, and reporting. No prior SAS experience needed. Enhance your data analysis capabilities with SQL querying and table joining. Develop proficiency in file structures and system commands. Start your SAS journey now.
This course is for users who want to learn how to write SAS programs to access, explore, prepare, and analyze data. It is the entry point to learning SAS programming for data science, machine learning, and artificial intelligence. It is a prerequisite to many other SAS courses.
By the end of this course, you will know how to use SAS Studio to write and submit SAS programs that access SAS, Microsoft Excel, and text data. You will know how to explore and validate data, prepare data by subsetting rows and computing new columns, analyze and report on data, export data and results to other formats, use SQL in SAS to query and join tables.
Prerequisites:
Learners should have experience using computer software. Specifically, you should be able to understand file structures and system commands on your operating systems and access data files on your operating systems. No prior SAS experience is needed.
What you will learn
Course Overview and Data Setup
In this module you learn about the course and you set up the data you need to do the practices in the course.
Essentials
In this module you learn how to use SAS programming tools and the fundamentals of SAS program structure and syntax.
Accessing Data
In this module, you learn to identify the features of a SAS table, access data through SAS libraries, and import data into SAS.
Exploring and Validating Data
In this module, you learn to use SAS procedures that provide insights about your data. You also learn to subset data so you can focus on particular segments, format data so you can easily understand it, and sort data to identify and resolve duplicate values.
Preparing Data
In this module, you learn how to do some common data manipulations, such as filtering rows and columns, computing new columns, and performing conditional processing.
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