Analytical talent is in high demand. In fact, Glassdoor recently ranked Data Science as the No. 1 job in America. With nearly 400 hours of learning content available, the SAS Academy for Data Science offers a comprehensive foundation for data science success.
Learn to manage big data, focusing on data quality and visual data exploration for advanced analytics, plus communication skills.
Get Course DetailsLearn analytical modeling, machine learning, experimentation, forecasting and optimization.
Get Course DetailsLearn it all. This program includes all coursework from both the big data and advanced analytics programs.
Get Course DetailsCritical SAS programming skills.
Exploring and visualizing data.
Working with Hadoop, Hive, Pig and SAS.
Fundamentals of statistics and analytics.
Improving data quality for reporting and analytics.
Accessing, transforming and manipulating data.
Essential communication skills.
Critical SAS programming skills.
Exploring and visualizing data.
Working with Hadoop, Hive, Pig and SAS.
Fundamentals of statistics and analytics.
Improving data quality for reporting and analytics.
Accessing, transforming and manipulating data.
Essential communication skills.
Critical SAS programming skills.
Exploring and visualizing data.
Working with Hadoop, Hive, Pig and SAS.
Fundamentals of statistics and analytics.
Improving data quality for reporting and analytics.
Accessing, transforming and manipulating data.
Essential communication skills.
Critical SAS programming skills.
Exploring and visualizing data.
Working with Hadoop, Hive, Pig and SAS.
Fundamentals of statistics and analytics.
Improving data quality for reporting and analytics.
Accessing, transforming and manipulating data.
Essential communication skills.
Machine learning and predictive modeling techniques.
Working with distributed and in-memory big data sets.
Pattern detection and experimentation in business.
Optimization techniques.
Time series forecasting.
Integrating SAS with R and Python.
Machine learning and predictive modeling techniques.
Working with distributed and in-memory big data sets.
Pattern detection and experimentation in business.
Optimization techniques.
Time series forecasting.
Integrating SAS with R and Python.
Machine learning and predictive modeling techniques.
Working with distributed and in-memory big data sets.
Pattern detection and experimentation in business.
Optimization techniques.
Time series forecasting.
Integrating SAS with R and Python.
Machine learning and predictive modeling techniques.
Working with distributed and in-memory big data sets.
Pattern detection and experimentation in business.
Optimization techniques.
Time series forecasting.
Integrating SAS with R and Python.
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