Machine Learning for decision makers




On demand


1 days

Sign up for this course


This Machine Learning course is for employees in managerial (technical and non-technical) and non-technical positions willing to deepen their knowledge on the possibilities of Machine Learning and how they can implement it in their own organisation.

Course outline

  • History and evolution of Machine Learning: Where do we come from and where are we now?
  • Main Machine Learning concepts
  • Introduction to supervised vs unsupervised learning


Supervised learning:

    • Regression
    • Classification
    • Deep Learning
    • Activity: possible applications of regression and classifications


Unsupervised learning:

    • Conceptual introduction
    • Activity: possible applications of unsupervised learning


Other Machine Learning related learning problems:

    • Optimization
    • Sorting
    • Reinforcement learning


Infrastructure in Machine Learning: 

    • Upscaling vs outscaling
    • Distributed computing
    • CPU vs GPU
    • How to estimate resource utilization


From lab to production:

    • Response times
    • Training serving skew
    • Online vs batch prediction


Planning a Machine Learning approach for a specific Use Case.


Final summary, discussion, Q&A, etc.

Sign up for this course