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Sii Poland

SII UKRAINE

SII SWEDEN

Send your request
Course objectives

Gaining the ability to manage the process of implementing solutions based on Machine Learning.

Benefits

Thanks to the training, the participant will be able to :

  • identify processes that can be optimized with Machine Learning
  • estimate the cost and return on investment of your Machine Learning solution
  • lead the Machine Learning implementation process
Training scope
  • Digital transformation – business consequences
  • When is it worth investing in Machine Learning? Scalability and algorithmization
  • Where to start? How to identify places where data-driven investment will bring the fastest and greatest growth?
  • Basic issues solved with Machine Learning
  • Overview of examples of usage models for solutions based on Machine Learning
  • Resources necessary to create ML solutions: data, people, computing power
  • Strategic decisions to be made: Inside the organization or outsourcing? Proof-of-concept or immediate solution?
  • Analysis of the profitability of introducing the ML solution
  • We do Machine Learning – a workshop based on a case study
Audience

Managers and specialists who would like to learn how to implement Machine Learning solutions in their organization.

Participation does not require machine learning knowledge.

Course objectives

Gaining the ability to manage the process of implementing solutions based on Machine Learning.

Benefits

Thanks to the training, the participant will be able to :

  • identify processes that can be optimized with Machine Learning
  • estimate the cost and return on investment of your Machine Learning solution
  • lead the Machine Learning implementation process
Training scope
  • Digital transformation – business consequences
  • When is it worth investing in Machine Learning? Scalability and algorithmization
  • Where to start? How to identify places where data-driven investment will bring the fastest and greatest growth?
  • Basic issues solved with Machine Learning
  • Overview of examples of usage models for solutions based on Machine Learning
  • Resources necessary to create ML solutions: data, people, computing power
  • Strategic decisions to be made: Inside the organization or outsourcing? Proof-of-concept or immediate solution?
  • Analysis of the profitability of introducing the ML solution
  • We do Machine Learning – a workshop based on a case study
Audience

Managers and specialists who would like to learn how to implement Machine Learning solutions in their organization.

Participation does not require machine learning knowledge.

The number of participants: 8-15 people

Duration: 2 days

Available language: PL / EN

Available course material: PL / EN

Course form
Presentation, lecture, discussion.

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Natalia & Agata

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Natalia & Agata

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