Objectives

• Participants will learn how to solve fault diagnosis and prediction problems in Mechatronic systems using Artificial Intelligence techniques. The course objective is to help participants decide whether Machine Learning (ML) is the right tool for their problem, what data would be needed to train the model and how to collect them, what ML model would be best for that specific problem, and how to implement it in Python.

Outcomes

Understand what Artificial Intelligence (AI) is about and when/how to use it to solve an engineering problem. Become familiar with Python, Neural Networks (NN), Machine Learning (ML), and Deep Learning (DL).Learn how to build and implement a ML/DL model using Python.

Course Contents

Day One:Introduction to Artificial Intelligence (AI).Hierarchy of AINeural NetworksMachine LearningDeep LearningReinforcement LearningHow to determine whether AI can solve my problem.ClassificationRegressionGenerationExamples of case studies using AI.Engineering related examplesDaily Life related examplesHow to determine/collect the required data.BrainstormingSensorsData AcquisitionData GovernanceLocal DatabaseCloud DatabaseDay Two:Python Fundamentals.Python InterpreterVariablesData typesData structuresInput/outputLooping & StatementsFor LoopWhile loopIf statementIntroduction to Object Oriented Programming (OOP).Encapsulation.Abstraction.Inheritance.Polymorphism.Python Coding ExamplesPractice TutorialDay Three:Artificial Neural NetworksMultilayer PerceptronLayers BackpropagationWeightsHow Machine Learning worksMappingGeneralizationMachine Learning algorithmsLinear RegressionDecision Tre

Description

Data will be available soon!