SAS Advanced explores the programming and analytical methods used to manage complex data, build predictive models, and present reliable findings. The course focuses on advanced SAS procedures, data preparation, macro programming, statistical analysis, reporting, and machine learning SAS workflows. It suits learners who need to move beyond basic syntax and apply SAS to structured business analysis, repeatable data processes, and model-driven decision-making.
SAS On Demand introduces the SAS environment for working with structured data, preparing datasets, and producing reliable statistical output. The course explores core SAS programming concepts, including data steps, procedures, data manipulation, reporting, and statistical analysis. It is suited to learners building practical SAS skills and preparing for topics associated with the SAS Certified Base Programmer pathway.
SAS Data Integration Studio is an ETL-focused course for building and managing data flows in the SAS environment. It examines data extraction, transformation, and loading workflows, including source-to-target mapping, job design, metadata management, and reusable transformations. The material helps learners understand how to prepare, integrate, and deliver data for reporting, analytics, and downstream business processes.
This SAS Predictive Modelling course examines how historical data is turned into reliable forecasts and decision models. Explore data preparation, variable selection, regression, classification, segmentation, model validation, and performance assessment using SAS analytics workflows. The material is suited to learners who want to apply data mining with SAS to practical prediction problems, interpret model results, and compare alternative modelling approaches for business and analytical use cases.
This SAS Business Analytics course examines how SAS supports the full business analysis workflow, from preparing and managing data to statistical analysis, reporting, and visualisation. Learn to use SAS programming concepts to investigate business trends, interpret analytical results, and present findings that inform operational, marketing, finance, and customer-focused decisions.
This financial analyst training focuses on applying SAS to the analytical work behind budgeting, forecasting, performance reporting, and financial data interpretation. Explore how to prepare and examine financial datasets, use SAS procedures for statistical analysis, build reliable reports, and communicate findings that support data-driven decision making. The course develops practical financial analysis skills for turning raw figures into clear business insight.
The Data Science with SAS Training from ZebLearn equips analysts with enterprise SAS skills for statistical analysis, machine learning, predictive modeling, text analytics, and visual data science using SAS Viya platform, SAS/STAT procedures, Visual Analytics, and Model Studio for regulated industries and production analytics. Master SAS Viya programming/model deployment, SAS/STAT (PROC REG/MIXED/LOGISTIC), Model Studio AutoML pipelines, Visual Analytics dashboards/interactive reports, text analytics/sentiment/topic modeling, time series forecasting (ES/ARIMA), SAS Visual Text Analytics, decision trees/gradient boosting/forest models, model comparison/selection, champion/challenger deployment, and regulatory compliance reporting to deliver validated, auditable data science solutions for finance, pharma, and government sectors.
The SAS Enterprise Guide Training from ZebLearn equips business analysts with intuitive GUI-based SAS analytics covering project management, Query Builder, data manipulation tasks, statistical analysis, reporting wizards, process flow diagrams, automation prompts, and multi-source data integration for rapid insights without coding. Master project creation/process flows, Query Builder (joins/filters/derived columns), data import/export, statistical tasks (ANOVA/regression/survival), reporting wizards, graph customization, task templates, conditional processing, and code generation enabling self-service analytics across Excel, databases, and SAS datasets with full audit trail.