Course
Introduction to LLMs in Python
IntermediateSkill Level
Updated 01/2026Start Course for Free
Included withPremium or Teams
PythonArtificial Intelligence3 hr11 videos34 Exercises2,700 XP28,969Statement of Accomplishment
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Training 2 or more people?
Try DataCamp for BusinessLoved by learners at thousands of companies
Course Description
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.
Feels like what you want to learn?
Start Course for FreeWhat 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
Prerequisites
Working with Hugging Face1
Getting Started with Large Language Models (LLMs)
2
Fine-tuning LLMs
3
Evaluating LLM performance
Introduction to LLMs in Python
Course Complete
Earn Statement of Accomplishment
Add this credential to your LinkedIn profile, resume, or CVShare it on social media and in your performance review
Included withPremium or Teams
Enroll NowFAQs
Join over 18 million learners and start Introduction to LLMs in Python today!
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.