Data Science›SAS
Master SAS — From Data Management to Advanced Analytics!
Learn SAS from scratch and advance to complex data analytics, reporting, and predictive modeling. This course provides hands-on experience with real-world datasets, ensuring you gain practical skills for business and data-driven decision-making.
About This Course
The SAS course covers the full spectrum of data analytics, from data manipulation and reporting to advanced analytics techniques like predictive modeling, regression analysis, and business intelligence dashboards. You'll gain expertise in Base SAS, SAS Macros, SQL, and SAS Enterprise Guide, preparing you for analytics roles across industries.
- Hours of Instructor-Led Training
- Hands-on Projects across Web, Data & AI
- Includes Beginner → Expert Level Topics
- Mentor Support, Assignments & Code Reviews
- Job Assistance & Portfolio Guidance
- Urbancode Certificate of Completion
What You'll Learn
Master SAS Programming
Learn data step, PROC SQL, SAS macros, and advanced programming concepts.
Data Management & Analytics
Manipulate, clean, and analyze large datasets efficiently.
Reporting & Visualization
Create dashboards, charts, and automated reports for business insights.
Predictive Modeling & Statistics
Apply regression, classification, and time series analysis using SAS.
Business Intelligence Skills
Build real-world BI projects using SAS Enterprise Guide.
Industry-Ready SAS Expertise
Gain practical skills applicable to analytics, data science, and BI roles.
Course Content
- Introduction to SAS and its applications
- Installing and navigating SAS environment
- Data types, variables, and datasets
- Basic SAS programming syntax
- Reading and writing datasets
- Debugging and error handling
- Data step basics and data manipulation
- Sorting, merging, and concatenating datasets
- Creating new variables and functions
- Conditional logic and loops in SAS
- Working with dates and character variables
- SAS Macros for automation
- SQL in SAS (PROC SQL)
- Arrays, Do loops, and iterative processing
- Advanced data manipulation techniques
- Error handling and debugging best practices
- Descriptive statistics and summary reports
- PROC MEANS, PROC FREQ, PROC UNIVARIATE
- Data visualization using PROC SGPLOT & PROC REPORT
- Generating automated reports
- Introduction to statistical procedures