Overview
Assess and strengthen their understanding of advanced Generative AI concepts., Recognize and mitigate bias, hallucinations, and ethical risks in Generative AI., Evaluate outputs for relevance, coherence, and compliance with responsible AI principles., Apply knowledge of architectures like transformers, GANs, VAEs, and diffusion models., Develop critical thinking to solve scenario-based questions about AI governance and deployment.
Students and professionals who want to test and deepen their knowledge of Generative AI., AI and machine learning practitioners looking to validate their understanding of advanced concepts., Learners who enjoy scenario-based, thought-provoking questions to strengthen critical thinking.
Basic understanding of Artificial Intelligence (AI) and Machine Learning concepts., Familiarity with common AI terminology (e.g., models, training, inference, datasets)., No programming skills required — but some exposure to AI tools or workflows is helpful.
Unlock the power of Generative AI with this comprehensive and challenging set of advanced questions designed to test and deepen your understanding of cutting-edge concepts. This collection is ideal for learners, practitioners, and professionals who want to assess and enhance their expertise in modern AI technologies.
You will encounter questions covering core topics like transformer architectures, GANs, VAEs, diffusion models, latent spaces, multimodal AI, fine-tuning, RLHF, MLOps, monitoring, bias mitigation, transparency, and responsible AI governance. These non-repetitive, advanced-level, scenario-based questions are crafted to test not just your knowledge but also your critical thinking and practical understanding of how Generative AI is applied in real-world domains such as healthcare, marketing, public sector, and software development.
Whether you're preparing for a certification, building a career in AI, or simply staying updated with the latest advancements, these questions help you validate your understanding of real-world generative AI systems. They challenge you to go beyond memorization, encouraging analytical thinking, ethical awareness, and deployment readiness in complex environments.
You’ll face practical scenarios, theoretical concepts, and conceptual drills that mirror what professionals encounter when working with generative models in business and industry. From ethical concerns like bias and hallucinations to technical challenges such as fine-tuning and monitoring outputs, these questions cover it all in a structured, learner-friendly format.
By working through these questions, you’ll gain a clearer grasp of both the power and pitfalls of generative AI — and the confidence to apply it effectively, responsibly, and creatively.
Syeda Begum
Syeda Begum — AWS/Azure/GCP Architect | CCDE | CCIEx5 (R&S, SP, Security, DC, Wireless) | CISSP | CISA | CISM | CRISC | ISO27001-LA
Syeda Begum is a distinguished Solution Architect based in Karachi, Pakistan, with over 18 years of global experience, including the last 10 years working extensively in Karachi’s dynamic technology landscape. She currently serves at a leading global telecommunications provider, where she designs and leads the implementation of complex, enterprise-scale technology architectures.
Over the past decade in Karachi, Syeda has partnered with major enterprises, public sector organizations, and service providers to deliver cutting-edge digital transformation initiatives, including cloud migrations, cybersecurity strategies, network modernization, and infrastructure optimization. Her approach is deeply consultative—she works closely with clients to understand their business processes and develops tailored, scalable, and secure technology solutions aligned with their strategic goals.