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Big Data Analytics with SAS

Big Data Analytics with SAS

The Fourth Industrial Revolution is upon us, even with the Third is still in progress. Big Data, Machine Learning and Artificial Intelligence are three of the driving forces behind it. While the term ‘Industrial Revolution’ has always applied mainly to manufacturing, it now also involves service industries such as banking and insurance, who are investing heavily in Big Data to help them model credit risk, fraud, marketing success and other key data. Meanwhile manufacturing, retail, telco, pharma and many other sectors constantly need people skilled in building, analysing, monitoring and maintaining data models to gain strategic intelligence that helps them inform and adapt their key business processes.

A leader in the world of Data Analytics is the SAS Institute, whose flagship product is SAS (Statistical Analysis System). It is now offering new courses in Advanced Analytics in a Big Data World, Credit Risk Modeling and Fraud Detection Using Descriptive, Predictive and Social Network Analytics.

Top minds in the Business Analytics world present the courses. They are professors at various universities and schools of management, who can be heard in person via classroom courses, interacted with in live web classrooms or learnt from in online-only eLearning format. The courses are not about the software itself but on general concepts and modeling techniques.

‘Advanced Analytics in a Big Data World’ covers Decision Trees, Regression Trees, key algorithms, Ensemble Methods, Neural Networks, Support Vector Machines, Bayesian Network Classifiers, Survival Analysis, Social Network Learning and Inference, Fuzzy Techniques and Evaluating Analytical Models. (That’s why it’s called “Advanced”).

‘Credit Risk Modeling’ deals with Basel I, Basel II and Basel III Regulations, Bankruptcy Prediction Models, LGD and EAD Models, Validation, Backtesting and Stress testing, Low Default Portfolios, and a number of other concepts involved in Credit Risk Modeling.

‘Fraud Detection Using Descriptive, Predictive, and Social Network Analytics’ includes Data Reprocessing, Social Networks for Fraud Detection, Neural Networks, Logistic Regression, and a lot more.

These look like go-to courses for those who make a living, or plan to make a living, out of Data Analytics.