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Layla Croll,
Laura Giles,
Chris Black,
Sandor Veres,
Sean Anderson,
Jonathan Aitken,
Noel Sharkey,
Mahnaz Arvaneh,
Natalie Wood,
Leonardo Stella,
and
Uziel Jaramillo-Avila
Topics Covered
- What a robot needs to be able to sense the world using drones, youBots and autonomous cars as examples.
- Current and future developments in robotics and how and where they are being applied.
- How robotics can take inspiration from nature looking at swarm robots and biomimetics.
- How robots work with others for example, a robot surgeon and a robotic arm.
Register for this course and see more details by visiting:
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Reviews summary
Robotics: ethics and societal impact
This course offers an overview of current and future robotics trends and developments. It also explores ethical challenges and opportunities that come with the growing presence of robotics in our lives. Students will learn about the potential benefits and risks of robotics, as well as the social and economic implications of this technology.
Combines perspectives from various disciplines.
"...a good introduction to the ethical issues related to living in an automated world."
"I enjoyed the intermix of videos and reading materials."
Provides insights into future applications of robotics.
"It built an understanding of the principles and fundamental challenges of designing robots including:"
"How robotics can take inspiration from nature..."
Provides a practical understanding of robotics.
"Most FutureLearn courses run multiple times."
"The course was both interesting and accessible..."
Examines the ethical and societal implications of robotics.
"This course looked at current and future developments in the field of robotics that could shape different aspects of people’s daily lives."
"...including engineers, designers, technicians and enthusiasts who are keen to explore the role of robots in our economic and industrial future."
May be too introductory for some learners.
"...wish there could be more science and terminology such as the chapter on game theory, instead of having too much literature and ethics."
Activities
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Building a Future with Robots.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Building a Future with Robots will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/n8uc7r/building
Reading list
We haven't picked any books for this reading list yet.
Comprehensive textbook on autonomous robotics, covering topics such as perception, planning, and control. It is suitable for graduate students.
Comprehensive textbook on probabilistic robotics, covering topics such as state estimation, planning, and control. It is suitable for graduate students.
Provides a comprehensive overview of robotics, covering topics such as kinematics, dynamics, control, and perception. It is suitable for both undergraduate and graduate students.
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Comprehensive textbook on robotics, covering a wide range of topics from kinematics to machine learning. It is suitable for both undergraduate and graduate students.
Provides a comprehensive overview of recent developments in robotic welding. It covers topics such as robotic welding processes, welding automation, and welding quality control.
Comprehensive textbook on robot modeling and control. It is suitable for both undergraduate and graduate students.
Mathematical introduction to robotics, covering topics such as kinematics, dynamics, and control. It is suitable for undergraduate students.
A comprehensive textbook that covers probabilistic graphical models (PGMs), a powerful tool for representing and reasoning about complex systems. Suitable for advanced learners with a background in probability and statistics.
A free online book that provides a gentle introduction to machine learning, covering topics such as linear regression, logistic regression, and neural networks. Suitable for beginners with no prior knowledge of AI or machine learning.
A practical guide to natural language processing (NLP) using Python, covering topics such as text classification, sentiment analysis, and machine translation. Suitable for beginners with some programming experience.
A classic textbook on reinforcement learning, a subfield of AI concerned with learning from interaction with the environment. Covers both theoretical concepts and practical algorithms, with a focus on real-world applications.
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A French-language textbook that focuses on machine learning, a subfield of AI. Covers topics such as supervised learning, unsupervised learning, and deep learning. Suitable for beginners with some programming experience.
A textbook that presents AI from a computational perspective, covering topics such as agents, knowledge representation, reasoning, and planning. Suitable for readers with a background in computer science or mathematics.
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A non-technical book that explores the global AI landscape, the impact of AI on society, and the ethical challenges that arise from the rapid development of AI technologies.
A short but powerful book that explores the potential benefits and risks of AI, as well as the ethical dilemmas that need to be addressed as AI becomes more advanced.
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A popular science book that discusses the development of AI algorithms and their potential impact on various aspects of human life, such as healthcare, transportation, and finance.
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A thought-provoking book that explores the potential implications of AI for human society, such as the possibility of a technological singularity and the need for new ethical frameworks.
A comprehensive German-language textbook that provides a broad overview of AI, covering topics such as search, knowledge representation, and machine learning. Suitable for both beginners and advanced learners.
Save
A highly cited and influential book that focuses on deep learning, a subfield of AI concerned with constructing models for complex data. Covers theoretical concepts, popular algorithms, and practical applications.
A comprehensive textbook that provides a broad overview of the field, covering topics such as problem-solving, learning, machine learning, and natural language processing. Suitable for both beginners and advanced learners.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/n8uc7r/building
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Time
9 hours
Via
FutureLearn
Institution
The University of Sheffield
Instructors
Layla Croll
Laura Giles
Chris Black
Sandor Veres
Sean Anderson
Jonathan Aitken
Noel Sharkey
Mahnaz Arvaneh
Natalie Wood
Leonardo Stella
Uziel Jaramillo-Avila
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