plores important concepts related to Large Language Models (LLMs), prompt engineering, AI security, and generative AI systems. The content is designed to help learners understand both the capabilities and limitations of modern AI technologies.
The series begins with prompt tuning, explaining how language models can be adapted and improved for specialized tasks without fully retraining the entire model. Learners discover how lightweight tuning techniques enhance AI performance efficiently.
A major focus is placed on the risks and limitations of large language models, including hallucinations, inaccurate outputs, bias, and reliability concerns. The lessons explain why AI systems sometimes generate false or misleading information and how these challenges affect real-world applications.
The course also explores zero-shot reasoning, demonstrating how modern LLMs can solve tasks and answer questions without task-specific training examples.
Additional topics include AI-powered language translation and how LLMs improve multilingual communication through contextual understanding and natural language generation.
Security is another important area covered in the series. Learners are introduced to prompt injection risks, adversarial manipulation, and security
