Introduction to Large Language Models

This clear, conceptual course explains how large language models work, covering tokenization, attention, pretraining, fine-tuning, and limitations like hallucination and bias. Learners will gain an intuition for how model architecture influences behaviour, and practical checklists for evaluating models and deploying them responsibly. The course includes simple demos to illustrate core mechanisms.

• Skills you’ll learn: tokenization, attention intuition, pretraining vs fine-tuning, safety considerations, deployment checklists.

Certificate: Certificate of completion provided upon finishing the course.

Requirements

• Basic programming literacy helpful but not required.

Who this course is for

• Students; curious professionals; developers new to LLMs.

Benefits

• Explain tokenization and attention; describe how LLMs generate text; discuss failure modes and safety; outline practical uses.