CSG202 — Generative Ai Fundamentals

The academic task covers the fundamentals of Generative AI, including its evolution, characteristics, and comparison with traditional machine learning. It assesses students' understanding of Large Language Models (LLMs), including transformer architecture, tokenization, embeddings, and inference. The assessment includes conceptual, analytical, and application-based questions based on the topics covered under CO1 and CO2.

Rubric
To assess students' understanding of the fundamental concepts of Generative AI, its differences from traditional machine learning, and the architecture, working principles, and real-world applications

Students will demonstrate the ability to design effective prompts in Vertex AI, analyze ethical issues in AI systems, explain Google's AI Principles and responsible innovation practices, and assess the role of AI governance, risk management, compliance, and stakeholder trust in developing trustworthy AI solutions.

Rubric
To evaluate students' understanding of prompt design using Vertex AI and their knowledge of Responsible AI principles, ethical AI practices, governance, and business applications.

Students will demonstrate the ability to explain the foundations and applications of Generative AI and LLMs, evaluate responsible AI principles and ethical considerations, describe prompt engineering and Vertex AI workflows, analyze AI governance and business implications, and interpret the use of advanced multimodal AI technologies for real-world problem-solving.

Rubric
To assess students' conceptual understanding of Generative AI, Large Language Models, Responsible AI principles, prompt design, Google Cloud AI practices, and advanced multimodal AI applications.