Associate Preparation for Generative AI and Large Language Models

Generative AI is reshaping the technological landscape, creating a high demand for professionals who understand the mechanics of Large Language Models (LLMs). This course provides a structured path to mastering the core concepts and practical applications of modern AI systems using industry-standard tools. You will transition from a basic understanding of artificial intelligence to a comprehensive grasp of how generative models are built, trained, and deployed. By focusing on the underlying hardware and software ecosystems, you will gain the technical literacy required to navigate the rapidly evolving field of deep learning. What you'll learn: - Understand the foundational concepts of Machine Learning, Deep Learning, and Neural Networks. - Analyze LLM architectures, including the transformer model and attention mechanisms. - Apply prompt engineering strategies to refine and control model behavior. - Explore Retrieval-Augmented Generation (RAG) for grounding AI responses in external data. - Learn the principles of model inference and deployment on high-performance hardware. - Evaluate ethical AI practices, including bias mitigation and safety protocols. This course begins with essential terminology and foundational definitions before progressing through the technical layers of generative models and deployment strategies. You will read through detailed explanations and analyze code snippets to solidify your understanding of the AI lifecycle. This course is designed for beginners who want a clear, text-based introduction to the world of generative AI, with no previous technical background required. Begin your journey into the world of Large Language Models now.