Overview
Use LoRA and QLoRA adapters to fine-tune BERT, GPT, Llama, Mistral and DeepSeek with minimal GPU memory., Run RLHF Direct Preference Optimization workflows to align model outputs with human feedback., Perform supervised instruction tuning to build domain datasets and update weights for task-specific accuracy gains., Compress large teachers into efficient students via knowledge distillation, transferring soft targets and hidden-feature signals.
Fine tune LLMs
Python, Basic of Generative AI
Master the complete spectrum of Large Language Model fine-tuning with the most comprehensive hands-on course available today. This intensive program transforms you from foundational concepts to enterprise-level deployment, covering cutting-edge techniques across multiple architectures and cloud platforms.
What You'll Learn
Advanced Fine-Tuning Methodologies:
Master LoRA (Low-Rank Adaptation) for parameter-efficient training that reduces computational costs while maintaining model performance23
Implement QLoRA (Quantized LoRA) for memory-optimized fine-tuning in resource-constrained environments
Deploy RLHF (Reinforcement Learning ) to create aligned AI systems that follow human preferences
Apply DPO (Direct Preference Optimization) for improved model behavior without complex reinforcement learning pipelines
Apply Model Distillation for Knowledge transfer from a large model to a smaller model
Multi-Architecture Model Training:
Fine-tune BERT models for specialized text understanding and classification tasks
Customize Mistral models for domain-specific applications requiring efficient performance
Adapt GPT architectures for conversational AI text generation systems
Optimize LLaMA models for professional-grade applications
Configure Cohere models for production-ready natural language processing workflows
Deploy on Hugging Face Hub: Master model uploading, versioning, and sharing using push_to_hub() functionality for seamless model distribution
Enterprise Cloud Platform Mastery:
Azure AI Foundry: Build, deploy, and manage enterprise-grade AI applications with integrated development environments
AWS Bedrock: Implement scalable fine-tuning workflows using S3, Lambda, and API Gateway for AI-powered applications
GCP Vertex AI: Leverage parameter-efficient tuning and full fine-tuning approaches with supervised learning methodologies
Key Learning Outcomes
Transform your AI expertise through hands-on projects that simulate real-world enterprise scenarios. Experience comprehensive dataset preparation, from raw data to production-ready training formats. Master performance optimization techniques including hyperparameter tuning, model evaluation metrics, and cost management strategies across cloud platforms. Build end-to-end deployment pipelines that scale from prototype to enterprise production environments.
Course Journey
Begin with transformer architecture fundamentals before progressing through parameter-efficient training methodologies. Each technique is reinforced through practical coding sessions using industry-standard datasets and real-world use cases. Experience comprehensive cloud platform integration across Azure, AWS, and GCP ecosystems, learning platform-specific optimization strategies and cross-platform migration techniques.
Who Should Enroll
Designed for intermediate to advanced AI practitioners, including machine learning engineers, data scientists, AI researchers, and software developers seeking specialization in LLM customization. Basic Python programming knowledge and familiarity with machine learning concepts are recommended.
Rahul Raj
Rahul Raj is Generative AI Engineer with over 10 years of experience in AI and software development. Over the past six years, He has been teaching students around the world and helping them understand complex AI concepts through practical, hands-on learning. He specializes in Generative AI, Large Language Models (LLMs), ChatGPT, LangChain, Python, Machine Learning, and Algorithmic Trading.
He is the Co-Founder of SRP AI Technology, where we build real-world AI applications for industries like healthcare, finance, and education. Along with product development, He also focus on supporting learners, developers, and entrepreneurs who want to grow their careers or businesses using AI.
His core teaching philosophy is to give people a future. He empowers students to be creators, not just consumers. He believe in using technology with wisdom, empathy, and purpose.His mission is to prepare the next generation to lead with knowledge,adapt with confidence, and build a world where humans and AI grow together
Whether you’re just getting started, switching careers, or looking to build your own AI projects or company, his courses are designed to guide you step-by-step through the most relevant tools and techniques used in the industry today.
If you're ready to build practical AI skills and stay ahead in this fast-moving field, He is here to help you every step of the way.