Products related to Employment:
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Talkabout Transitions : From Education to Employment
This is a comprehensive programme of activities designed to support young people as they make the transition from education to employment.Following the hugely successful TALKABOUT structure, the programme is broken down into topics and activities, each constructed to teach the skills necessary for further education or employment.Topics explore the various opportunities available to school leavers, offer guidance on the application and interview processes and consider the skills necessary to make employment a success.Exploring transition as a process of discovery, this programme takes the fear and uncertainty out of this time of change.The resource includes: Assessment and evaluation forms to help assess the needs of the individual and personalise the programme 40 engaging activities Fully photocopiable and downloadable colour resources to facilitate group sessions This book is an invaluable resource for professionals working with teenagers and young adults with SEMH needs, autism spectrum disorders and intellectual disabilities.The programme would also benefit teenagers and young people daunted by change or struggling to find or remain in employment.
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Employment
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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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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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Is there an education voucher for an SGD distance learning course from the Federal Employment Agency?
Yes, the Federal Employment Agency in Germany offers education vouchers for distance learning courses, including those offered by SGD (Studiengemeinschaft Darmstadt). These vouchers can be used to cover the costs of the course fees, materials, and other related expenses. To qualify for the voucher, individuals must meet certain eligibility criteria set by the agency. It is recommended to contact the Federal Employment Agency directly for more information on how to apply for an education voucher for an SGD distance learning course.
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Employment Law
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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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EU Employment Law
This new edition of EU Employment Law provides a complete revision and update of the leading English language text in the field.The coverage in the new edition has been expanded with material on all the latest developments, incorporating the changes made by the Lisbon Treaty; the EU2020 strategy; the Charter of Fundamental Rights; the 'Article 19 Directives'; the Temporary Agency Work Directive; the revisions to the existing including the Directives on Parental Leave and European Works Council; and the new Social Security Regulations 883/2004.It also analyses the ever-expanding body of employment case law, including the momentous decisions in Viking, Laval, Rueffert, and Commission v Luxembourg. The book begins with an examination of the development of EU employment law focusing on the shift from employment law to employment policy.The text then studies rule-making in the field of employment law, considering both the traditional routes to legislation and governance techniques such as the Open Method of Coordination.The final chapters look closely at the substantive area of employment law, examining the free movement of persons, equal treatment, health and safety and working conditions, the restructuring of enterprises, worker participation, and collective action.Throughout, the book addresses the fundamental question as to the purpose of EU employment law: is it primarily economic, or social, or both?
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Employment Law 9e
Packed with a wealth of case law and legislation, this book will enable you to fully understand the intricacies of this fast-changing subject with ease.With features such as chapter summaries and further reading suggestions, Employment Law is well-suited to support you in your studies. The ninth edition has been fully updated to include coverage of the latest legislative and case law developments, including: issues around shared parental leave;the national living wage;legal developments in the area of non-standard work. Offering comprehensive coverage of all the key aspects of individual and collective employment law in a clear and accessible way, Employment Law is ideal for both LLB and HRM students.
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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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What types of employment references are there: qualified employment reference or simple employment reference?
There are two types of employment references: qualified employment references and simple employment references. A qualified employment reference is provided by someone who has directly supervised or worked closely with the individual, and can speak to their skills, abilities, and work performance. On the other hand, a simple employment reference is typically provided by someone who may not have worked closely with the individual, such as a colleague or HR representative, and can only confirm basic details like job title and dates of employment. Qualified employment references are generally more valuable to potential employers as they provide more detailed insights into the candidate's capabilities.
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How can one learn to become an electronics technician for industrial engineering or automation technology?
To become an electronics technician for industrial engineering or automation technology, one can start by pursuing a relevant educational program, such as an associate degree in electronics engineering technology or industrial automation. These programs typically cover topics such as electrical circuits, industrial control systems, and automation technologies. Additionally, gaining hands-on experience through internships or apprenticeships with companies in the industrial engineering or automation field can provide valuable practical skills. Seeking professional certifications, such as those offered by organizations like the International Society of Automation (ISA) or the Electronics Technicians Association (ETA), can also demonstrate expertise and knowledge in the field. Finally, staying updated with the latest advancements in industrial engineering and automation technology through continuous learning and professional development is essential for a successful career in this field.
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Is artificial intelligence an opportunity or a risk for learning in school?
Artificial intelligence can be both an opportunity and a risk for learning in school. On one hand, AI can personalize learning experiences, provide instant feedback, and offer additional resources to support student learning. This can enhance student engagement and understanding. However, there are also concerns about the potential for AI to replace teachers, compromise student privacy, and perpetuate biases in the learning process. Therefore, it is important for educators to carefully consider how to integrate AI into the classroom in a way that maximizes its benefits while minimizing its risks.
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