Generative AI & LLMs: From Zero to Practical AI Mastery

About this course

This course contains the use of artificial intelligence.

Generative AI & LLMs: From Zero to Practical AI MasteryGenerative AI and Large Language Models are transforming how people learn, work, create, analyze information, and solve problems. But using tools like ChatGPT effectively requires more than knowing how to type a prompt.

This course takes you from the fundamentals of language models to practical, responsible use of Generative AI, without requiring you to become a machine-learning engineer.

You will learn what actually happens inside an LLM, why transformers changed language AI, how models learn, how prompting works, where LLMs are genuinely useful, and where their limitations create risk.

What will you learn?

You will begin by understanding why LLMs are such a significant development in AI and how we arrived at today's technology—from rule-based systems to machine learning, deep learning, transformers, and large language models.

You will then learn what a language model actually is. Instead of treating an LLM as a mysterious black box, you will understand the fundamental idea of predicting likely continuations from context and how this simple concept scales into surprisingly powerful capabilities.

Next, you will explore the core building blocks of LLMs, including:

• Tokens and tokenization
• Embeddings and numerical representations
• Context and context windows
• Parameters and model size
• Pre-training
• Fine-tuning and instruction-tuning
• Inference

From there, the course goes inside the Transformer architecture. You will learn why transformers became so important, how self-attention works conceptually, what queries, keys, and values represent, why multi-head attention is useful, and how layers, residual conne

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