Final assessment (Pilot)

Type of course:

Digital learning, Lesson

Language:

Duration:

5 minutes

Proficiency:

Intermediate

Target:

Professionals

SUMMARY

We have now completed the training. Before we finish, we’d like to suggest a final test to validate what you’ve learned. This test will be in the form of an MCQ, and will cover all the concepts covered during the course: time series analysis, time series decomposition, acquisition, processing, modeling, model deployment…

About The Author

Killian Niel is a data scientist and a pedagogical engineer at the Ecole de Génie Industriel of Grenoble INP in France. He is particularly attracted to the application of machine learning to solve industrial problems. He is interested in confidentiality issues in the field of artificial intelligence and carried out a research and development project about privacy-preserving machine learning techniques for a SME.

Learning outcomes

By the end of this lesson, students will be able to identify examples of technical-commercial problems that can be solved using data science.
By the end of this lesson, students will be able to demonstrate the use of tools for predicting offer and demand.
By the end of this lesson, students will be able to explain the evolution of quotation approaches and cost estimation survey.