Type of course:
Digital learning, Path
Language:
EN
Duration:
2 hours, 20 minutes
Workload:
6 hours
Proficiency:
Advanced
Target:
Professionals, Students
This Learning Path explores artificial intelligence and deep learning with a specific focus on manufacturing applications. Explore topics such as predictive maintenance for Electrical Machining, performance evaluation of machine learning and deep learning models applied to demand forecasting and preference learning, quality control, and anomaly detection in production, and harnessing natural language processing (NLP) for improved traceability of requirements within design documentation and testing suites, all as integral components of the MANTIS project. Acquire the expertise needed to leverage deep learning for optimizing manufacturing processes and enhancing product quality in this rapidly evolving industry.
Learning outcomes
- The learner will be able to effectively reduce noise in data to enhance data quality and accuracy.
- The learner will be able to identify suitable methods and algorithms, including logistic regression, neural networks (NN), and convolutional neural networks (CNN), for comprehensive data analysis across diverse tools and scenarios.
- The learner will be able to apply one-class classifiers to implement statistical process control techniques in real-world contexts.
LessonDL modelling for demand forecast
Course Content
LessonQuality control and anomaly detection in production
Course Content
LessonNatural language processing (NLP) for more consistent traceability of requirements into design documentation and testing suites
Course Content
LessonDeep Learning quiz of AI for Manufacturing
Course Content
Topics
Digital Transformation, Artificial Intelligence (AI)