8546 modules
Page 56
-
PSYC3083 2029-30
AI Applications in Psychology
This module will provide an overview of how machine learning and Artificial Intelligence can be used to answer questions in different fields of psychology. -
PSYC3083 2027-28
AI Applications in Psychology
This module will provide an overview of how machine learning and Artificial Intelligence can be used to answer questions in different fields of psychology. -
PSYC6178 2026-27
AI Applications in Psychology
This module will provide an overview of how machine learning and Artificial Intelligence can be used to answer questions in different fields of psychology. -
PSYC3083 2026-27
AI Applications in Psychology
This module will provide an overview of how machine learning and Artificial Intelligence can be used to answer questions in different fields of psychology. -
PSYC3083 2028-29
AI Applications in Psychology
This module will provide an overview of how machine learning and Artificial Intelligence can be used to answer questions in different fields of psychology. -
MANG6585 2025-26
AI Ethics and Sustainability
This course focuses on the ethical integration and applications of Artificial Intelligence (AI) in business settings, with a specific emphasis on the challenges and opportunities related to algorithmic bias, inequalities, and diversity management as part of social sustainability. Taking a holistic approach to sustainability, students will explore the theoretical concepts and practical applications to understand how AI technologies can perpetuate or mitigate biases, create environmental issues and how this is all linked to economic sustainability. Based on critical evaluation of case studies regarding AI-induced inequalities, students will learn how to develop strategies for managing diversity and apply ethical frameworks to AI development and implementation. -
MANG6585 2026-27
AI Ethics and Sustainability
This course focuses on the ethical integration and applications of Artificial Intelligence (AI) in business settings, with a specific emphasis on the challenges and opportunities related to algorithmic bias, inequalities, and diversity management as part of social sustainability. Taking a holistic approach to sustainability, students will explore the theoretical concepts and practical applications to understand how AI technologies can perpetuate or mitigate biases, create environmental issues and how this is all linked to economic sustainability. Based on critical evaluation of case studies regarding AI-induced inequalities, students will learn how to develop strategies for managing diversity and apply ethical frameworks to AI development and implementation. -
SUST6002 2026-27
AI for Sustainability Techniques and Research Methods
This module focuses on AI technologies and its applications within sustainability. The core aim is to develop a conceptual understanding of the research challenges for the SustAI CDT themes. This will help to build a common language among the cohort, enabling them to work more effectively together. The module draws heavily on research, case studies and tutorials delivered by academics as well as our partners in industry, government and the third sector. -
SUST6002 2025-26
AI for Sustainability Techniques and Research Methods
This module focuses on AI technologies and its applications within sustainability. The core aim is to develop a conceptual understanding of the research challenges for the SustAI CDT themes. This will help to build a common language among the cohort, enabling them to work more effectively together. The module draws heavily on research, case studies and tutorials delivered by academics as well as our partners in industry, government and the third sector. -
MANG2113 2027-28
AI in Business and Society – Ethics and Sustainability
This course focuses on the ethical integration and applications of Artificial Intelligence (AI) in business settings, with a specific emphasis on the challenges and opportunities related to algorithmic bias, inequalities, and diversity management as part of social sustainability. Taking a holistic approach to sustainability, students will explore the theoretical concepts and practical applications to understand how AI technologies can perpetuate or mitigate biases, create environmental issues and how this is all linked to economic sustainability. Based on a critical evaluation of case studies regarding AI-induced inequalities, students will learn how to develop strategies for managing diversity and apply ethical frameworks to AI development and implementation.