Transform open-source language models into domain-specific powerhouses. This advanced course teaches you to fine-tune Mistral and Llama models on proprietary data using cutting-edge techniques like LoRA and QLoRA. You'll navigate the complete pipeline—from data preparation and quality assurance to optimised deployment—with production patterns, error handling strategies, and architectural decisions used in real enterprises. Throughout eight intensive lessons, you'll build a sophisticated legal document analyser that understands contract terminology, regulatory frameworks, and nuanced legal concepts. Learn to handle edge cases, manage computational constraints, monitor model performance, and implement robust evaluation frameworks that ensure your fine-tuned models deliver reliable results in production environments. This course bridges the gap between theoretical fine-tuning concepts and battle-tested implementation strategies. You'll gain hands-on experience with industry-standard tools, learn cost-optimisation techniques, and understand when to fine-tune versus when to leverage retrieval-augmented generation or prompt engineering instead.

Lessons

  1. Foundation: Fine-Tuning Theory & Architecture Decisions — Understanding LoRA, QLoRA, full fine-tuning trade-offs, and when to choose each approach for production systems (+150 XP)
  2. Domain Data Preparation: Quality, Scale & Validation — Building robust pipelines for legal document collection, annotation, deduplication, and quality assurance with edge case handling (+160 XP)
  3. Advanced Training Techniques & Optimisation — Curriculum learning, mixed-precision training, gradient checkpointing, and cost-effective multi-GPU strategies for resource-constrained environments (+170 XP)
  4. Building the Legal Analyser: Implementation & Production Patterns — End-to-end implementation with error handling, logging, checkpoint management, and handling training failures gracefully (+180 XP)
  5. Evaluation Frameworks: Beyond Standard Metrics — Custom evaluation pipelines for legal domains, human-in-the-loop assessment, domain-expert validation, and robustness testing (+165 XP)
  6. Deployment & Inference Optimisation — Model quantisation, ONNX conversion, real-time serving architecture, batching strategies, and latency optimisation for production inference (+175 XP)
  7. Monitoring, Maintenance & Continuous Improvement — Production monitoring systems, performance drift detection, feedback loops, retraining strategies, and versioning for long-term model governance (+155 XP)
  8. Capstone: Deploy Your Legal Document Analyser at Scale — Integrating all concepts to deploy a production-grade system with proper error handling, monitoring, and real-world architectural patterns (+200 XP)