​🔍 Fine-Tuning LLMs for Real-World Use Cases

​​Fine-tuning is no longer just for big labs. In this session, we’ll explore how you can take large language models and tailor them to your specific domain; efficiently, reliably, and with real impact.

​🎯 Agenda

​🧠 Fine-Tuning Fundamentals
Master the art of adapting pre-trained models with your own data. We’ll cover cutting-edge, parameter-efficient methods like LoRA and QLoRA that dramatically lower compute costs while preserving quality.

​📊 Data Strategy & Curation
The model is only as good as the data. Learn how to design high-quality datasets through cleaning, augmentation, and synthetic generation, ensuring your model truly understands your domain.

​🧪 Evaluation Framework Design
Accuracy isn’t enough. Discover how to build custom evaluation metrics and benchmarks that align with what success actually looks like for your use case.

​⚙️ Production Integration Patterns
From dev to deployment; get practical insights into integrating fine-tuned models into real products. We’ll discuss patterns for latency optimization, scalability, versioning, and long-term maintainability.

​👥 Who Should Attend

​AI Application Developers, researchers, founders, and builders who want to move beyond prompt engineering and unlock the full potential of LLM customization.

​📍 Location

​Online — Via Google Meet. https://meet.google.com/fyn-njbm-cwp

​🗓 Date & Time

​Friday, 11 April. 7:00 PM > 8:00PM (GMT +5:30)