Applied LLM and Prompt Eng Bootcamp

Service Description

Course Structure This hands-on, intensive bootcamp is designed to take participants from LLM fundamentals to building production-ready AI applications using modern prompt engineering and applied LLM techniques. Module 1 — Foundations of Applied LLMs Objective: Build a strong conceptual foundation -Introduction to Large Language Models (LLMs) -How LLMs actually work (tokens, embeddings, transformers) -Capabilities vs limitations of LLMs -Common use cases and real-world applications -LLM architecture overview -Prompt engineering fundamentals Module 2 — Prompt Engineering Fundamentals Objective: Learn core prompting techniques -Prompt structure and components -Zero-shot vs Few-shot prompting -Role prompting & system instructions -Prompt chaining -Output formatting & control -Reducing hallucinations Module 3 — Advanced Prompt Engineering Objective: Master advanced prompting strategies -Chain-of-thought prompting -Self-consistency prompting -ReAct prompting -Multi-step reasoning prompts -Guardrails and prompt safety -Prompt optimization techniques Module 4 — Retrieval Augmented Generation (RAG) Objective: Build LLMs that use your own data -Introduction to RAG architecture -Embeddings and vector databases -Chunking strategies -Retrieval optimization -RAG evaluation Module 5 — Building Applied LLM Applications Objective: Move from prompts to applications -LLM application architecture -Chatbots & assistants -Document automation -Knowledge assistants -Workflow automation Module 6 — LLM Tooling & Agents Objective: Build intelligent LLM-powered agents -Tool calling and function calling -Agent architectures -Multi-agent systems -Planning and reasoning agents Module 7 — Evaluation & Optimization Objective: Improve reliability and performance -LLM evaluation techniques -Prompt testing frameworks -Performance optimization -Latency & cost optimization -Prompt versioning Module 8 — Production & Deployment Objective: Deploy real-world LLM systems -LLM deployment architecture -API integration -Scaling LLM applications -Monitoring & logging -Security & governance Who Should Attend -AI Engineers -Developers -Data Scientists -Product Managers -Technical Leaders -Automation Engineers Learning Outcomes By the end of this bootcamp, participants will: -Master prompt engineering -Build real-world LLM applications -Implement RAG systems -Create AI agents -Deploy production-ready solutions