This module provides an in-depth exploration of Generative AI, offering participants a foundational understanding of its core concepts, technologies, and real-world applications. By the end of this module, participants will be equipped to define generative AI, recognize the key technologies that enable it, and understand its potential for mimicking human creativity and thinking through pattern recognition and content generation.
By the end of this module, the participants will be able to:

• Learning Objective 1 -LO1: define generative AI and explain its primary purpose (CO1).
• Learning Objective 2 - LO2: identify and describe the core technologies underpinning generative AI, including neural networks, transformers, and diffusion models (CO1).
• Learning Objective 3 - LO3: illustrate how generative AI mimics human thinking and creativity using examples of pattern recognition and content generation (CO1).
• Learning Objective 4- LO4: list at least three applications of generative AI and explain how it executes complex tasks like text generation or image synthesis (CO1).

This module focuses on exploring the transformative role of generative AI across various industries, emphasizing its real-world applications, ethical challenges, and practical solutions. Learners will delve into how generative AI is being utilized in sectors such as healthcare, creative industries, business, and education, examining real-world use cases to understand its potential to enhance decision-making, solve complex problems, and drive innovation. The module also highlights key ethical considerations, including concerns around misinformation, bias, and intellectual property, encouraging learners to critically assess these challenges and propose strategies to mitigate risks. 
By the end of this module, the participants will be able to:

• Learning Objective 5-LO5: identify key applications of generative AI in diverse industries such as healthcare, creative industries, business, and education (CO2).
• Learning Objective 6-LO6: describe how generative AI is applied in specific scenarios, including AI-assisted medical diagnostics, automated content creation, and personalized education (CO2).
• Learning Objective 7-LO7: explain how generative AI contributes to solving complex problems, such as developing personalized treatment plans or adapting content for individual learning needs (CO2).
• Learning Objective 8 -LO8: analyze ethical challenges in generative AI, including the creation of misleading content, intellectual property concerns, and addressing biases in AI outputs (CO2).
• Learning Objective 9- LO9: propose strategies to mitigate ethical and practical issues in generative AI, such as using diverse training data, implementing robust filtering mechanisms, and conducting regular audits (CO2).
• Learning Objective 10-LO10: evaluate the transformative impact of generative AI across various domains, balancing its benefits with ethical considerations (CO2).
• Learning Objective 11-LO11: apply their understanding of generative AI to analyze real-world case studies and propose innovative applications or improvements in specific industries (CO2).

This module focuses on the practical applications of generative AI tools in the field of education, equipping participants with the skills to create dynamic, customized learning materials and experiences. Participants will explore key AI-powered tools for text generation, visual media creation, and audio/video production, enabling them to generate lesson plans, summaries, quizzes, and other educational content tailored to diverse skill levels.

By the end of this module, the participants will be able to:

• Learning Objective 12-LO12: identify and describe the capabilities of key generative AI tools for text generation, visual media creation, and audio/video production (CO3).
• Learning Objective 13-LO13:demonstrate how to use GPT-based tools to generate lesson plans, summaries, quizzes, and other educational content tailored to various skill levels (CO3).
• Learning Objective 14- LO14: apply tools like DALL-E to create custom educational visuals, including diagrams, infographics, and illustrations, to enhance learning materials (CO3).
• Learning Objective 15-LO15: use AI-powered voiceover tools and automated video creation platforms to develop engaging multimedia content for online learning (CO3).

This module explores the societal and educational implications of generative AI, focusing on its transformative effects on workplaces and learning environments. Participants will evaluate how AI is reshaping industries through automation, innovation, and role redefinition, with a particular emphasis on its applications in sectors like HR, healthcare, and business analytics.

By the end of this module, the participants will be able to:

• Learning Objective 16- LO16 :evaluate how generative AI is reshaping workplaces and educational systems through automation, innovation, and role redefinition (CO4).
• Learning Objective 17-LO17 :describe how AI-powered tools are automating routine tasks and enabling decision-support systems in industries like HR, healthcare, and business analytics (CO4).
• Learning Objective 18- LO18:explore the impact of AI on learning environments, including the use of adaptive learning systems, intelligent tutoring, and the evolving role of educators (CO4).
• Learning Objective 19- LO19:identify ethical and privacy risks associated with generative AI, such as data breaches, misinformation, and potential misuse in academic or professional settings (CO4).
• Learning Objective 20- LO20:propose strategies to address data security risks, prevent misinformation, and ensure transparency in the use of generative AI tools (CO4).
• Learning Objective 21- LO21:analyze the benefits of AI-human collaboration in various domains and identify strategies to maintain the right balance between AI integration and human input (CO4).
• Learning Objective 22- LO22:develop strategies for educational institutions to adapt to AI integration, including curriculum (CO4).
• Learning Objective 23- LO23:outline principles for establishing ethical guidelines that govern the integration of AI in education and the workplace (CO4).
• Learning Objective 24- LO24:emphasize the importance of teaching AI literacy to students and educators, promoting responsible use and critical evaluation of AI systems (CO4).