Modeling of Autonomous Systems
About this course
This course will explain the core structure in any autonomous system which includes sensors, actuators, and potentially communication networks. Then, it will cover different formal modeling frameworks used for autonomous systems including state-space representations (difference or differential equations), timed automata, hybrid automata, and in general transition systems. It will describe solutions and behaviors of systems and different interconnections between systems. This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
83/100
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- What the provider tells you
- 32/45
- Who stands behind it
- 35/35
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- 16/20
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What you'll learn
- understanding of sensors and actuators in autonomous systems
- familiarity with formal modeling frameworks
- ability to describe solutions and behaviors of systems
- knowledge of interconnections between systems
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