Course
Introduction to LLMs in Python
IntermediateSkill Level
Updated 01/2026
PythonArtificial Intelligence3 hr11 videos34 Exercises2,700 XP32,199Statement of Accomplishment
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Uncover What's Behind the Large Language Models Hype
Large Language Models (LLMs) have become pivotal tools driving some of the most stunning advancements and applications in today's AI landscape. This hands-on course will equip you with the practical knowledge and skills needed to understand, build, and harness the power of LLMs for solving complex language tasks such as translation, language generation, and more.
Discover LLM Architecture and Leverage Pre-Trained Models
Through interactive coding exercises, you'll discover different transformer architectures and how to identify them. You'll explore leveraging pre-trained language models and datasets from Hugging Face for fine-tuning and evaluating your model using advanced metrics that fit LLMs. Finally, you'll find out more about ethical and bias concerns relevant to LLMs and ways to identify these. By the end of this course, you will be able to build LLMs, fine-tune, and evaluate them using specialized metrics while understanding the key challenges and ethical considerations of enabling real-world LLM applications.
What you'll learn
- Define the end-to-end workflow for fine-tuning a pre-trained LLM with Hugging Face
- Differentiate practical techniques to mitigate bias, hallucination, and other ethical risks when deploying LLMs
- Distinguish between encoder-only, decoder-only, and encoder-decoder transformer architectures
- Evaluate model performance by selecting and interpreting appropriate metrics such as accuracy, BLEU, ROUGE, perplexity, and toxicity
- Identify the primary language tasks large language models can perform and the Hugging Face tools used to run them
Feels like what you want to learn?
Start Course for FreePrerequisites
Working with Hugging Face1
Getting Started with Large Language Models (LLMs)
Begin your journey with Large Language Models (LLMs) by understanding what they are and what they can do, and peek under the hood to get an idea of how they work!
2
Fine-tuning LLMs
Learn how to leverage pre-trained LLMs and datasets from Hugging Face to fine-tune a model.
3
Evaluating LLM performance
Dive into different metrics to assess model performance and wrap up by learning about the challenges of applying LLMs in the real world.
Introduction to LLMs in Python
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FAQs
Do I need prior knowledge of LLMs or transformers?
No, you don't need much prior knowledge on LLMs or transformers. This course will need you to be familiar with navigating the Hugging Face Hub and deep learning models. It will discuss transformer architecture at a high-level to help you understand the different structures available.
What tools will I use during the course?
You will use Hugging Face’s pre-trained models and datasets, along with Python, to work on practical coding exercises. You won't be using any APIs.
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