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MBSE

Model-Based Systems Engineering

This course is a part of Digital Manufacturing & Design Technology , a 9-course Specialization series from Coursera.

This Model-Based Systems Engineering (MBSE) course and the Digital Thread courses featured earlier in this specialization bring together the concepts from across digital manufacturing and design, forming a vision in which the geometry of a product is just one way of describing it. MBSE is where the model resulting from the evolution of system requirements, design, analysis, verification and validation activities is the focus of design and manufacturing. Students will gain an understanding of systems engineering, the model-based approach to design and manufacturing, the Digital Twin, and a roadmap toward a model-based enterprise. Students will be able to explain the value and expectations of systems engineering and model-based systems engineering, and the underlying motivations and opportunities represented by a model-based enterprise. They will develop the knowledge necessary to perform a baseline assessment of an organization’s potential to leverage MBSE. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the eighth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA

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University at Buffalo

Rating 4.4 based on 19 ratings
Length 5 weeks
Effort 4 weeks of study, 3 ½ hours per week
Starts Apr 22 (5 weeks ago)
Cost $49
From University at Buffalo, The State University of New York via Coursera
Instructor Ken English
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Engineering Programming
Tags Data Science Physical Science And Engineering Mechanical Engineering Machine Learning

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What people are saying

We analyzed reviews for this course to surface learners' thoughts about it

course is awesome in one review

THE COURSE IS AWESOME It was more theoretical and less practical.I expected more of a real-time approach that can broaden my understanding MBSE.

also suggest how in one review

It provides MBSE concept in very simple approach and also suggest how systematically we can assess the MBE practices in the organization and follow recommended practices at different level to reach ultimate goal.

broaden my understanding in one review

evaluation quizzes mark in one review

The evaluation quizzes mark wrong for the correct answers and I would like to know the reason for the same.

major fields related in one review

G To less information about SysML and Effect Chains thank you for the course Gives a clear idea about MBSE covering basics of all the major fields related to MBSE and MBE.

reach ultimate goal in one review

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Engineering Systems Coordinator $84k

Systems Engineering Representative $84k

Systems Engineering Level 0 $92k

Engineering Systems Specialist $102k

Systems Engineering 4 $108k

Systems Engineering and Integration $108k

Systems Support Engineering $115k

Systems and Network Engineering $119k

Regional Systems Engineering $125k

Enterprise Systems Engineering $140k

Systems Engineering Officer $155k

Systems Engineering Architect $188k

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Coursera

&

University at Buffalo

Rating 4.4 based on 19 ratings
Length 5 weeks
Effort 4 weeks of study, 3 ½ hours per week
Starts Apr 22 (5 weeks ago)
Cost $49
From University at Buffalo, The State University of New York via Coursera
Instructor Ken English
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Engineering Programming
Tags Data Science Physical Science And Engineering Mechanical Engineering Machine Learning

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