Introduction to LLMs in Python

Across about three hours of interactive exercises you identify transformer architectures, pull pre-trained models and datasets from Hugging Face, and fine-tune models yourself — genuinely hands-on, and aimed at people who can already code Python and want to work with LLMs directly rather than conceptually.

Two practical notes before you dive in. Fine-tuning anything sizeable needs paid GPU compute, a cost separate from your DataCamp subscription that's easy to overlook until the bill arrives. And the LLM ecosystem moves fast, so check the libraries still match current versions. The course itself is on DataCamp's subscription (about $14/month billed annually, first chapter free), certificate of completion included as a learning record (as of 2026).

Introduction to LLMs in Python turns LLM theory into working code. Across about three hours of interactive exercises you identify different transformer architectures, use pre-trained models and datasets from Hugging Face, and fine-tune and evaluate models for tasks like translation and text generation.