Focus on this objective today: Optimize through fine-tuning: Prepare data for fine-tuning. Explain it in your own words, apply it to one realistic scenario, and verify the details against the official source. Source context: Read in English Optimize and fine-tune AI agents for production Module 8 Units Feedback Intermediate Data Scientist AI Engineer Microsoft Foundry Learn to evaluate and select fine-tuning methods, recognize agent quality problems, prepare training data, and design optimization strategies using hyperparameter configuration and iterative evaluation. Learning objectives By the end of this module, you'll be able to: Evaluate and select fine-tuning methods including supervised fine-tuning (SFT), reinforcement fine-tuning (RFT), and direct preference optimization (DPO) based on quality requirements, data availability, and cost constraints. Recognize agent quality problems and determine which fine-tuning approach addresses the root cause for format inconsistency, tone misalignment, or reasoning failures.
Objective
Optimize through fine-tuning: Prepare data for fine-tuning