Prescriptive Analytics Training in Bradford

Prescriptive Analytics Training in Bradford

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.

NobleProg onsite live Prescriptive Analytics training courses are aimed at business analysts and Business Intelligence (BI) teams .

Prescriptive Analytics training is available in various formats, including onsite live training and live instructor-led training using an interactive, remote desktop setup. Local Prescriptive Analytics training can be carried out live on customer premises or in NobleProg local training centers.

Bradford - Carlisle Business Centre

Carlisle Business Centre
60 Carlisle Road
Bradford, WYK BD8 8BD
United Kingdom
West Yorkshire GB
Bradford - Carlisle Business Centre
Carlisle Business Centre is a not for private profit organisation, driven by a dedicated workforce, that's supported by a voluntary board of directors. We...Read more

Prescriptive Analytics Course Events - Bradford

Code Name Venue Duration Course Date PHP Course Price [Remote / Classroom]
matlabpredanalytics Matlab for Predictive Analytics Bradford - Carlisle Business Centre 21 hours Mon, 2018-03-26 09:30 £3300 / £4050
matlabprescriptive Matlab for Prescriptive Analytics Bradford - Carlisle Business Centre 14 hours Wed, 2018-04-25 09:30 £2200 / £2700
matlabpredanalytics Matlab for Predictive Analytics Bradford - Carlisle Business Centre 21 hours Wed, 2018-05-30 09:30 £3300 / £4050
matlabprescriptive Matlab for Prescriptive Analytics Bradford - Carlisle Business Centre 14 hours Thu, 2018-06-14 09:30 £2200 / £2700
matlabpredanalytics Matlab for Predictive Analytics Bradford - Carlisle Business Centre 21 hours Tue, 2018-07-31 09:30 £3300 / £4050

Course Outlines

Code Name Duration Outline
matlabpredanalytics Matlab for Predictive Analytics 21 hours

Predictive analytics is the process of using data analytics to make predictions about the future. This process uses data along with data mining, statistics, and machine learning techniques to create a predictive model for forecasting future events.

In this instructor-led, live training, participants will learn how to use Matlab to build predictive models and apply them to large sample data sets to predict future events based on the data.

By the end of this training, participants will be able to:

  • Create predictive models to analyze patterns in historical and transactional data
  • Use predictive modeling to identify risks and opportunities
  • Build mathematical models that capture important trends
  • Use data to from devices and business systems to reduce waste, save time, or cut costs

Audience

  • Developers
  • Engineers
  • Domain experts

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice
matlabprescriptive Matlab for Prescriptive Analytics 14 hours

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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