TransformAIx

LLM & Advanced AI Training

Master Large Language Models & Cutting-Edge AI Technologies

Duration

3-5 Days

Format

Hands-On Technical

Target Audience

AI Engineers & Developers

Level

Intermediate to Advanced

About This Program

Our LLM & Advanced AI Training provides deep technical expertise in large language models, transformer architectures, and state-of-the-art AI technologies. This comprehensive program covers everything from foundational concepts to advanced implementation techniques, including fine-tuning, prompt engineering, RAG systems, and deployment strategies. You'll gain hands-on experience with leading LLM platforms and learn to build production-ready AI applications.

        Key Learning Outcomes
        Master transformer architectures and attention mechanisms
Build and fine-tune large language models for specific use cases
Implement advanced prompt engineering and chain-of-thought techniques
Design and deploy RAG (Retrieval-Augmented Generation) systems
Optimize LLM performance, cost, and latency
Understand safety, alignment, and ethical considerations

    

Who Should Attend

AI/ML Engineers & Researchers
Data Scientists & Analysts
Software Developers
NLP Specialists

Tech Leads & Architects
Product Managers (Technical)
Research Scientists
AI Consultants

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Module 1: LLM Fundamentals & Architecture

Transformer architecture deep dive: self-attention, multi-head attention
Understanding GPT, BERT, T5, and modern architectures
Tokenization strategies and vocabulary design
Pre-training vs. fine-tuning vs. prompting paradigms
Model scale: parameters, compute, and emergent abilities

Module 2: Advanced Prompt Engineering & LLM APIs

Prompt design patterns and best practices
Chain-of-thought, few-shot, and zero-shot learning
Using OpenAI, Anthropic, Google, and open-source LLMs
Function calling and structured outputs
Building conversational agents and chatbots

Module 3: Fine-Tuning & RAG Systems

Fine-tuning techniques: full fine-tuning vs. LoRA vs. PEFT
Dataset preparation and quality for fine-tuning
RAG architectures: vector databases, embedding models, retrieval
Building production RAG pipelines with LangChain/LlamaIndex
Hybrid approaches: combining retrieval, fine-tuning, and prompting

Module 4: Deployment, Optimization & Safety

Model serving and inference optimization (quantization, caching)
Cost optimization strategies for LLM applications
Monitoring, evaluation, and observability
Safety, alignment, and guardrails implementation
Real-world case studies and hands-on capstone project

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Cutting-Edge Content: Updated with latest LLM research and techniques
Hands-On Labs: 60% of time spent coding and building
Real Datasets: Work with production-scale data
Expert Instructors: Engineers from leading AI companies

Best Practices: Learn from production deployments
Tool Agnostic: Cover multiple frameworks and platforms
Capstone Project: Build your own LLM application
Community Access: Join our AI practitioners network

Program Includes
            Comprehensive code repository
Pre-configured development environments
LLM evaluation frameworks
Prompt engineering library

            Access to GPU compute credits
Video recordings of all sessions
1-month post-training support
Certificate of completion

        

Ready to Master LLMs?

Join the next generation of AI engineers building transformative applications with large language models.
Let's discuss how this program can accelerate your AI career.

Email Us

contact@transformaix.in

Call Us

+91 8983010800

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LLM & Advanced AI Training

Program Overview

About This Program

Key Learning Outcomes

Who Should Attend

Program Curriculum

Why Choose TransformAIx

Program Includes

Ready to Master LLMs?