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Data Analytics and Machine Learning for Manufacturing: fundamentals (part 2)

By Grenoble INP – UGA - Grenoble INP – UGA

Type of course:

Digital learning, Path

Language:

EN

Duration:

5 hours

Workload:

6 hours

Proficiency:

Advanced

Target:

Manager, Professionals, Workers

This course provides a comprehensive introduction to data analytics and machine learning techniques essential for manufacturing. Participants will learn to build and evaluate linear and logistic regression models, implement regression projects, and classify data using Bayes networks and other classifiers. Practical skills are developed through hands-on projects, including generating HTML files, ensuring participants can apply these techniques effectively in real-world manufacturing scenarios. The course culminates with a final assessment to solidify understanding and application of the concepts learned.


Learning outcomes

  1. Identify the roles of stakeholders in a data analytics project.
  2. Manipulate data and perform basic data analysis.
  3. Build models to classify data or to predict a numeric value.
LessonSupervised method chapter evaluation

Topics

Digital Transformation, Artificial Intelligence (AI), Data Analytics

Provided by

Content created in 2021
+225 enrolled
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Course Includes

  • 1 Quiz
  • 1 Certificate of achievement

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