The SAS BKS Series offers effective courses developed and delivered by leading industry experts, including Advanced Analytics for the Modern Business Analyst, Data Mining: Principles and Best Practices, Net Lift Models, Survival Data Mining, and Text Analytics. Check out our fall classes!
Learn how to use data mining effectively and harvest its advantages.
The SAS® Business Knowledge Series hosts a variety of courses developed and delivered by leading industry experts. Check out our fall classes!
Advanced Analytics for the Modern Business Analyst
delivers a unique learning experience that will provide analysts with the tools to succeed in a highly analytical and data-driven economy.
Analytics: Putting It All to Work
addresses how you can cope with the problem of information overload and create real business value from your data.
Applying Survival Analysis to Business Time-to-Event Problems
shows you how to calculate the future value of your customers by understanding their behaviors that have a time-to-event component using SAS® Enterprise Guide®.
Data Mining: Principles and Best Practices, introduces the power and potential of data mining and shows you how to discover useful patterns and trends from your data.
Data Mining Techniques: Theory and Practice
explores the inner workings of data mining techniques and how to make them work for you.
Exploratory Analysis for Large and Complex Problems Using SAS® Enterprise Miner™
presents highly pragmatic and practical methods to help analysts deal with the magnitude of data present in today's complex problems.
Net Lift Models: Optimizing the Impact of Your Marketing Efforts
demonstrates how to build Net Lift Models that optimize the incremental impact of marketing campaigns, covering the pros and cons of various core analytical approaches.
Survival Data Mining: Predictive Hazard Modeling for Customer History Data
identifies the benefits and pitfalls of using survival analysis for business intelligence.
Text Analytics and Sentiment Mining Using SAS®
will help you organize, manage, and mine textual data to generate customer insights and to understand and predict customer sentiments.