Navigating the LLM Landscape: A Practical Implementation Guide for Engineers

Join us for a focused, engineer-friendly deep-dive into modern Large Language Models (LLMs) and their practical applications in network engineering, operations, and automation. This weekly workshop series is designed to give participants hands-on knowledge, real deployment insights, and actionable skills. 

 Instructor  

 Mohammed Bakheet https://www.linkedin.com/in/mrabkoo/   

 Who Should Join? 

 Network engineers, cloud engineers, systems operators, students in ICT, and anyone interested in practical AI applications in technical operations. 

 Workshop Topics 

 1. Prompt Engineering Learn how to craft effective prompts to get accurate, reliable, and context-aware outputs from LLMs. We cover: 

 

 Prompt structure and templates 

 System vs. user instructions 

 Prompt optimization techniques 

 Avoiding hallucinations 

 

 2. RAG (Retrieval-Augmented Generation) Pipelines Understand how to integrate your own data sources with LLMs to deliver accurate and domain-specific responses. We cover: 

 

 Vector embeddings 

 Knowledge bases 

 Architecture patterns for production RAG 

 

 3. Fine-tuning LLMs Dive into customizing LLMs for your environment, dataset, or operational workflows. We cover: 

 

 Types of fine-tuning (SFT, LoRA, QLoRA) 

 Data preparation 

 Training workflows 

 Evaluating and validating tuned models 

 

 4. AI Agents Explore how AI agents can automate tasks, perform reasoning, and integrate with systems and APIs. We cover: 

 

 Multi-step task execution 

 Tool calling 

 Agent architectures 

 Practical use cases for NOGs and ISPs 

 

 Why Attend? 

 

 Hands-on, practical focus 

 Real examples from engineering and operations 

 Learn how to deploy and use LLMs effectively in your environment 

 Open discussion, demos, and shared learning with the sdnog community 

 

 Session's record 

 https://drive.google.com/file/d/1_FUkQgAddEermA45m-1FYyx8tNQi6Itx/view?usp=share_link