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Learning Innovation and the Future of Higher Education
Giving higher education professionals the language and tools they need to seize new opportunities in digital learning. A quiet revolution is sweeping across US colleges and universities.As schools rethink how students learn - both inside and outside the classroom - technology is changing not only what should be taught but how best to teach it.From active learning and inclusive pedagogy to online and hybrid courses, traditional institutions are leveraging their fundamental strengths while challenging long-standing assumptions about how teaching and learning happen.At this intersection of learning, technology, design, and organizational change lies the foundation of a new academic discipline of digital learning.Coalescing around this new field of study is a common critical language, along with a set of theoretical frameworks, methodological practices, and shared challenges and goals.In Learning Innovation and the Future of Higher Education, Joshua Kim and Edward Maloney explore the context of this new discipline, show how it exists within a larger body of scholarship, and give examples of how this scholarship is being used on campuses. What Kim and Maloney demonstrate in this foundational text is an understanding that change is a complex dynamic between what happens in the classroom and the larger institutional structures and traditions at play.Ultimately, the authors make a compelling case not only for this turn to learning but also for creating new pathways for nonfaculty learning careers, understanding the limits of professional organizations and social media, and the need to establish this new interdisciplinary field of learning innovation.
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Learn Autonomous Programming with Python : Utilize Python’s capabilities in artificial intelligence, machine learning, deep learning and robotic process automation
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Food Engineering Automation with Robotics and AI
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Artificial Intelligence and Learning Futures : Critical Narratives of Technology and Imagination in Higher Education
Artificial Intelligence and Learning Futures: Critical Narratives of Technology and Imagination in Higher Education explores the implications of artificial intelligence’s adoption in higher education and the challenges to building sustainable instead of dystopic schooling.As AI becomes integral to both pedagogy and profitability in today’s colleges and universities, a critical discourse on these systems and algorithms is urgently needed to push back against their potential to enable surveillance, control, and oppression.This book examines the development, risks, and opportunities inherent to AI in education and curriculum design, the problematic ideological assumptions of intelligence and technology, and the evidence base and ethical imagination required to responsibly implement these learning technologies in a way that ensures quality and sustainability.Leaders, administrators, and faculty as well as technologists and designers will find these provocative and accessible ideas profoundly applicable to their research, decision-making, and concerns.
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Which programming language is used for robotics and artificial intelligence?
Python is commonly used for robotics and artificial intelligence due to its simplicity, readability, and extensive libraries for machine learning and robotics. It is also known for its flexibility and ease of integration with hardware, making it a popular choice for developing robotics and AI applications. Additionally, Python's strong community support and active development make it a suitable language for these rapidly evolving fields.
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Is machine learning already artificial intelligence?
Machine learning is a subset of artificial intelligence. It involves training a machine to learn from data and make predictions or decisions without being explicitly programmed to do so. Artificial intelligence, on the other hand, encompasses a broader range of technologies and applications that enable machines to perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, and solving problems. While machine learning is an important component of artificial intelligence, AI also includes other techniques such as natural language processing, computer vision, and robotics.
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How difficult is a study of robotics and automation?
The study of robotics and automation can be challenging due to its interdisciplinary nature, requiring knowledge in fields such as mechanical engineering, electrical engineering, computer science, and control systems. Additionally, the rapid advancements in technology and the need to stay updated with the latest developments can add to the complexity of the study. However, with dedication, problem-solving skills, and a strong foundation in mathematics and physics, students can overcome these challenges and excel in the field of robotics and automation.
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How can we minimize the negative impacts of technologies such as artificial intelligence and robotics on the workforce?
To minimize the negative impacts of technologies such as artificial intelligence and robotics on the workforce, it is important to invest in retraining and upskilling programs for workers whose jobs may be displaced. This will help them transition into new roles that require human skills that cannot be easily replaced by machines. Additionally, implementing policies that support job creation in emerging industries and providing support for workers who are displaced will help mitigate the negative impacts. It is also crucial to have ongoing dialogue between policymakers, industry leaders, and workers to ensure that the workforce is prepared for the changes brought about by these technologies.
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Artificial Intelligence : From Machine Learning to Super-Intelligence and the Singularity
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Advances in Robotics and Artificial Intelligence
The reality of autonomous machines with artificial intelligence is becoming more real every day.The ability of machines to think and learn fascinates everyone, but now even the most reluctant readers have a chance to engage in learning about the history and future of robotics.This book covers everything from the 18th century French automatons to Ada Lovelace and Alan Turing, from self-driving cars and smart homes to assembly and military robots.Each spread is complimented with vivid artwork that further illuminates the accessible, exciting text.
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Plug-and-Play Education : Knowledge and Learning in the Age of Platforms and Artificial Intelligence
Plug-and-Play Education: Knowledge and Learning in the Age of Platforms and Artificial Intelligence documents and critiques how the education sector is changing with the advancement of ubiquitous edtech platforms and automation.As programmability and computation reengineer institutions towards efficiency and prediction, the perpetual collection of and access to digital data is creating complex opportunities and concerns.Drawing from research into secondary and higher education settings, this book examines the influence of digital “infrastructuring”, the automation of teaching and learning, and the very purpose of education in a context of growing platformisation and artificial intelligence integration.These theoretical, practical, and policy-oriented insights will offer educational technologists, designers, researchers, and policymakers a more inclusive, diverse, and open-ended perspective on the design and implementation of learning technologies.
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The Ultimate Modern Guide to Artificial Intelligence : Including Machine Learning, Deep Learning, IoT, Data Science, Robotics, The Future of Jobs, Required Upskilling and Intelligent Industries
This book is your ultimate guide to understanding the revolutionary technology of Artificial Intelligence (AI).This book covers everything from the basics of AI to its profound impact on various industries, such as healthcare, transportation, banking, and entertainment.You will discover the endless possibilities of AI and how it is changing our lives for the better. The book begins with an introduction to AI and its significance in the modern world.You will learn about the various applications of AI, including speech recognition assistants, image recognition, and biometric data analysis.This will give you a comprehensive understanding of how AI is used in our daily lives and the different industries benefiting from its advancements. In the following chapters, you will delve deeper into the workings of AI, machine learning, deep learning, neural networks, and natural language generation.The book explains how these technologies function and how they are applied in real-life scenarios.You will also gain insights into the differences between human and machine intelligence, providing a holistic understanding of AI's capabilities and limitations. Whether you are a business decision-maker, an IT professional, or someone who is merely interested in the impact of AI on the world, this book is a must-read.With its easy-to-understand language and numerous examples, it empowers you to comprehend the complex technology of AI and be part of the conversation shaping our future.
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Is programming taught in the field of Electrical Engineering and Information Technology?
Yes, programming is taught in the field of Electrical Engineering and Information Technology. Both fields require a strong foundation in programming languages such as C, C++, Python, and Java to develop software, design hardware, and work with embedded systems. Programming skills are essential for designing and implementing various electrical and information technology systems, including control systems, communication networks, and digital signal processing. Additionally, understanding programming concepts is crucial for developing innovative solutions and advancing technology in these fields.
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How could society of tomorrow look like as artificial intelligence and automation continue to advance?
As artificial intelligence and automation continue to advance, the society of tomorrow could see significant changes in various aspects of life. There may be increased efficiency and productivity in industries, leading to a shift in the job market and the need for new skill sets. There could also be advancements in healthcare, transportation, and communication, improving the overall quality of life. However, there may also be concerns about job displacement and the ethical implications of AI, leading to a need for new regulations and policies to ensure a fair and equitable society. Overall, the society of tomorrow could be more technologically advanced, but it will also require careful consideration of the social and ethical impacts of these advancements.
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Is the technical diploma in automation technology difficult?
The difficulty of the technical diploma in automation technology can vary depending on the individual's background, experience, and aptitude for the subject matter. Some students may find the coursework challenging due to the complex concepts and technical skills required, while others with a strong foundation in math, science, and technology may find it more manageable. Overall, dedication, hard work, and a genuine interest in automation technology can help students succeed in completing the program.
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Is the electronics technician for automation technology difficult?
Becoming an electronics technician for automation technology can be challenging, as it requires a strong understanding of electrical systems, programming, and automation technology. The field is constantly evolving, so technicians must stay updated on the latest advancements and technologies. However, with dedication and the right training, individuals can develop the skills and knowledge needed to succeed in this role. It may be difficult at times, but the opportunities for growth and the potential to work on cutting-edge technology make it a rewarding career choice for those passionate about automation.
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