MC11: Tokenization and Processing Data for Fine-Tuning is a specialized masterclass under the AI Residency program designed to equip participants with the foundational skills required to prepare high-quality datasets for model customization.

In this session, learners will explore the principles of tokenization, data formatting, and preprocessing techniques essential for fine-tuning Large Language Models (LLMs). The masterclass covers how raw text is transformed into model-ready inputs, best practices for dataset cleaning and structuring, and strategies for optimizing training performance. Participants will gain practical expertise in preparing data pipelines that support efficient, accurate, and scalable fine-tuning workflows.

This masterclass is part of the AI Residency.

✅ Join the new AI Residency cohort starting Jul 11 to build this end-to-end with guided support, project feedback, and a production-ready workflow—from data ingestion → indexing → retrieval → evaluation → deployment.

https://academy.decodingdatascience.com/airesidencyfasttrack