What a great learning experience! The flow of information was excellent, and the practical exercises were key. Very happy with this.
SAS Programming Foundations for Data Analysis
Learn to write SAS programs to access, explore, and prepare data for analysis and data science workflows without any prior programming experience.
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About this course
Data is the backbone of modern decision-making, but raw data is rarely ready for analysis. SAS is a trusted global standard for data management, and learning how to program with it opens doors to powerful data science and analytics workflows.
This text-based course guides you from absolute beginner to confidently writing your own SAS programs. You will learn how to read different data sources, clean and restructure datasets, and generate clear summary reports.
What you'll learn:
- Understand foundational SAS syntax, rules, and the structure of DATA and PROC steps.
- Access and import data from various formats, including Excel spreadsheets, text files, and modern structured data.
- Explore and validate datasets to identify missing values, duplicates, and data quality issues.
- Prepare and transform data by filtering rows, selecting columns, and creating new variables.
- Analyze data using basic statistical procedures and generate clear, readable reports.
- Apply clean coding practices and debugging techniques to troubleshoot program errors.
You will start with core terminology and syntax rules before moving step-by-step through importing, cleaning, and analyzing real-world data scenarios.
This course is designed entirely for beginners, and no prior programming or data analysis experience is required.
Start reading today to build a strong foundation in SAS programming and take control of your data.
Course contents
6 modules · 30 lessons · 3h 18m
1
Introduction and Syntax Fundamentals
Understand the general structure of SAS programs and basic writing rules.
- Why SAS? Its Importance in Decision Making
Learn about SAS's role as a global standard for data management and analysis.6 min - Program Structure: The Difference Between DATA and PROC
Understand the two fundamental building blocks of any SAS program: the DATA step and the PROC step.7 min - Syntax Rules: Semicolons and Reserved Words
Learn the strict rules for writing code to avoid syntax errors.6 min - Libraries: Where Does Your Data Live?
How to define paths and access stored datasets.7 min - Clean Coding Practices and Comments
The importance of organizing code and writing notes to make the program readable.6 min
2
Accessing and Importing Data
Bring data from various external sources into the SAS environment.
- Manually Entering Data Using DATALINES
A quick way to create small tables directly within the code.6 min - Importing Text and CSV Files
Using PROC IMPORT to read data from simple text files.7 min - Working with Excel Files
How to successfully convert Excel spreadsheets into SAS datasets.7 min - Reading Structured and Modern Data
Handling data formats ready for analysis.6 min - Troubleshooting Common Import Errors
How to proceed when an external file is not read correctly.7 min
3
Exploring Data and Checking Its Quality
Examine data to identify problems before starting analysis.
- Inspecting Data Structure with PROC CONTENTS
Learn variable names, types, and table properties.6 min - Detecting Missing Values
Identify gaps in data that may affect the accuracy of results.7 min - Handling Duplicate Data with PROC SORT
Using NODUPKEY options to clean the table from duplicates.7 min - Viewing Data for Preview with PROC PRINT
Using selective printing to visually confirm the correctness of values.6 min - Checking Value Ranges and Quality
Ensuring that data falls within expected logical boundaries.7 min
4
Transforming and Preparing Data
Modify and restructure data to suit analysis needs.
- Selecting Columns: KEEP and DROP
Select only necessary variables to reduce data size and increase efficiency.6 min - Filtering Rows Using WHERE
Extract a subset of data based on specific conditions.7 min - Creating New Calculated Variables
Perform mathematical operations to produce new metrics from raw data.7 min - Conditional Logic: IF-THEN/ELSE
Classify data and create categorical variables based on logical conditions.7 min - Formatting Variables (Formats & Labels)
Improve data appearance and label variables with understandable names.6 min - Real-World Scenario: Preparing Sales Data
A practical application combining filtering and transformation skills in one exercise.7 min
5
Statistical Analysis and Reporting
Extract insights from data and present them in reports.
- Descriptive Statistics with PROC MEANS
Calculate averages, standard deviations, and extreme values.7 min - Frequency Analysis with PROC FREQ
Create frequency tables for categorical data.7 min - Creating Clear Summary Reports
Compile results into easy-to-read tables for managers.6 min - Enhancing Reports: Titles and Footnotes
Add TITLE and FOOTNOTE to make reports look professional.6 min - Exporting Results to External Files
How to send final reports to formats like PDF or HTML.7 min
6
Debugging and Advanced Practices
Understand the SAS log and efficiently solve programming problems.
- Reading the SAS Log
Understand the difference between Notes, Warnings, and Errors.7 min - Common Syntax Errors and How to Resolve Them
Dealing with missing semicolons and unclosed parentheses.7 min - Logical Errors: When Code Runs with Incorrect Results
How to trace code to discover why results are not as expected.6 min - Final Review: The Ideal Workflow in SAS
A summary of best practices from import to final report.7 min
Final project
Comprehensive Customer Data Analysis Project
You will import a raw customer data file, clean the data from duplicates and missing values, create new variables for customer segmentation, then perform statistical analysis and produce a formatted final report.
What you'll get
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Short & focused
3h 18m of practical content
Certificate of completion
Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.
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Certificate of Mastery
This certifies that
Name Surname
has successfully demonstrated mastery of
SAS Programming Foundations for Data Analysis
Skills demonstrated
✓
Behavioral pattern analysis
Foundational
1.2 hrs
✓
Decision-architecture frameworks
Proficient
1.4 hrs
✓
A/B test design
Proficient
1.7 hrs
✓
Behavioral copywriting
Advanced
1.9 hrs
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SAS Programming Foundations for Data Analysis
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Performance detail
Coursework summary
Lessons completed
14 / 14
Practice questions
26 / 28
Assignments submitted
4 (avg 4.5 / 5)
Capstone project
Reviewed — 4.6 / 5
Total practice
6.2 hrs
Performance benchmark
Cohort rank
Top 12% of 1,625
Time to completion
11 days (median: 22)
Mastery score
91 / 100
Practice-question score
94%
Skill verification
Verified Skill Path
Reviews (12)
Seriously impressed! The real-world examples made everything so clear. Definitely a valuable addition to my skillset.
It's a good course if you have some prior knowledge. For absolute beginners, some concepts might be a bit challenging. The structure is logical, though.
Thoroughly enjoyed this course. The way the information was presented was excellent, and the practical applications were highlighted effectively. Great job!
Wow, this was exactly what I needed. The pace was perfect and the examples really helped solidify the concepts. So glad I took this.
Pretty good introduction. The examples were helpful, but I wish there was a bit more practice material. Solid value for the cost.
This was a good introduction. The structure is logical, and it covers the basics effectively. Might be too introductory for advanced learners.
So well-structured and easy to follow. I especially appreciated the real-world examples.
A good introduction. The structure was mostly clear, but I wish there were a few more real-world examples. Still, learned a lot.
So glad I took this. It provided a solid foundation and the practical applications discussed are immediately useful. Great value.
Decent introduction. The structure was logical, but I wish there had been more hands-on practice beyond the basic examples.
Hmm, I'm not sure this is for absolute beginners. It assumes a bit of prior knowledge that wasn't explicitly taught. Some examples were confusing.
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