Introduction to Large Language Models

The “Introduction to Large Language Models” course offers a clear and engaging overview of one of today’s most transformative areas in artificial intelligence. It’s designed for learners who want to understand how LLMs like ChatGPT, Gemini, and Claude work — and how they can be applied in real-world scenarios.

The course begins with the basics of natural language processing (NLP) and gradually builds up to explain the Transformer architecture, the foundation of modern LLMs. The explanations are concise but insightful, helping students grasp key ideas such as self-attention, tokenization, and fine-tuning.

One of the strongest points of the course is its practical focus. Through hands-on labs and demonstrations, learners can see how prompts, parameters, and model outputs interact in real time. The lessons on prompt engineering and responsible AI practices are especially valuable — they bridge the gap between theory and practical use.

By the end, students not only understand how LLMs generate text, summarize content, and assist in creative or analytical tasks, but also gain awareness of their limitations — such as bias, misinformation, and ethical challenges.

Overall, this course is a great starting point for anyone interested in generative AI. It balances theory and practice well, and provides the foundation needed to explore more advanced topics like fine-tuning, reinforcement learning from human feedback (RLHF), or integrating LLMs into applications.