Prescriptive Analytics Training in Reading

Prescriptive Analytics Training in Reading

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.

Reading TVP

Reading Tames Valley Park
400 Thames Valley Park Drive Thames Valley Park
Reading, BRK RG6 1PT
United Kingdom
Berkshire GB
Reading TVP
The Thames Valley Park business centre is in a prestigious, modern 200-acre business park and nature reserve idyllically positioned close to the south bank of...Read more

Prescriptive Analytics Course Events - Reading

Code Name Venue Duration Course Date PHP Course Price [Remote / Classroom]
matlabprescriptive Matlab for Prescriptive Analytics Reading TVP 14 hours Tue, 2018-02-06 09:30 £2200 / £2730
matlabpredanalytics Matlab for Predictive Analytics Reading TVP 21 hours Tue, 2018-03-20 09:30 £3300 / £4095
matlabprescriptive Matlab for Prescriptive Analytics Reading TVP 14 hours Wed, 2018-04-04 09:30 £2200 / £2730
matlabpredanalytics Matlab for Predictive Analytics Reading TVP 21 hours Wed, 2018-05-23 09:30 £3300 / £4095
matlabprescriptive Matlab for Prescriptive Analytics Reading TVP 14 hours Tue, 2018-06-05 09:30 £2200 / £2730
matlabpredanalytics Matlab for Predictive Analytics Reading TVP 21 hours Wed, 2018-07-18 09:30 £3300 / £4095
matlabprescriptive Matlab for Prescriptive Analytics Reading TVP 14 hours Mon, 2018-07-30 09:30 £2200 / £2730

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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