Type of course:
Digital learning, Lesson
Language:
EN
Duration:
5 minutes
Proficiency:
Intermediate
Target:
Professionals
SUMMARY
In the previous lesson, we saw examples of commercial applications, whether for automating certain repetitive tasks or improving customer contact management.
Now we’re going to look at examples of AI applications for commercial service in industry. Finally, we present a summary of this course.

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.
Course Content
Topics
Uncategorized
Tags
Machine learning, manufaturing data