Online or onsite, instructor-led live Prescriptive Analytics training courses are aimed at business analysts and Business Intelligence (BI) teams .
Prescriptive Analytics training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Prescriptive Analytics trainings in Almada can be carried out locally on customer premises or in NobleProg corporate training centers.
"A perfect getaway about 30 minutes from Lisbon". Disconnect from the world and discover the Mercure Lisboa Almada Hotel. Thi...
"A perfect getaway about 30 minutes from Lisbon". Disconnect from the world and discover the Mercure Lisboa Almada Hotel. This 4-star hotel set in a green zone overlooks the Tagus River and the mythical Cristo Rei. A short drive away, relax on beautiful Costa da Caparica beaches. There is a modern restaurant with a wide variety of natural fruit juices and mocktails, plus 4 fully equipped meeting rooms.
Prescriptive analytics is a branch of business analytics, together with descriptive and predictive analytics. It uses predictive models to suggest actions to take for optimal outcomes, relying on optimization and rules-based techniques as a basis for decision making.
In this instructor-led, live training, participants will learn how to use Matlab to carry out prescriptive analytics on a set of sample data.
By the end of this training, participants will be able to:
Understand the key concepts and frameworks used in prescriptive analytics
Use MATLAB and its toolboxes to acquire, clean and explore data
Use rules-based techniques including inference engines, scorecards, and decision trees to make decisions based on different business scenarios
Use Monte Carlo simulation to analyze uncertainties and ensure sound decision making
Deploy predictive and prescriptive models to enterprise systems
Audience
Business analysts
Operations planners
Functional managers
BI (Business Intelligence) team members
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
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