Getting Started with LLMs – 1 Day Workshop in London

Tue, 23 Dec, 2025 at 09:00 am to Tue, 09 Jun, 2026 at 05:00 pm UTC-05:00

Regus ON, London – London City Centre | London

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Publisher/HostCatils_inc
Getting Started with LLMs \u2013 1 Day Workshop in London
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Demystify LLMs and learn step-by-step how to use them for real-world tasks, projects, productivity, and innovation.
About this Event

Group Discounts:

  • Save 10% when registering 3 or more participants
  • Save 15% when registering 10 or more participants

Duration: 1 Full Day (9:00 AM – 5:00 PM)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs / Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, beverages, and light snacks included


Course Overview

This introductory and practical program provides a clear understanding of how Large Language Models (LLMs) such as ChatGPT and open-source transformer models work. Participants will explore model structure, prompting techniques, model fine-tuning, and integration workflows. Through guided exercises and real project demos, attendees will develop confidence in building and applying LLM-powered solutions across business functions and industry use cases.

Learning Objectives

By the end of this course, you will be able to:

  • Explain how LLMs and transformer models work
  • Design clear and optimized prompts
  • Customize or adapt models for specific tasks
  • Integrate LLM capabilities into real applications
  • Identify and evaluate business use cases
  • Apply responsible governance and data standards

Target Audience

  • Developers & Software Engineers
  • Data Scientists & Technical Professionals
  • Product & Innovation Teams
  • Business Analysts & Consultants
  • Anyone exploring applied AI workflows

Why Choose This Course?

Most professionals and organizations are exploring LLMs but lack the clarity and structure to use them effectively and responsibly. This course breaks down complex AI concepts into simple, practical steps you can immediately apply at work. You gain not just knowledge — but confidence to build and deploy real solutions.

©2025 Catils. This content is protected by copyright law. Copy or Reproduction without permission is prohibited.


Want to build a stronger AI culture across your organization?
In-house programs are available to align with your team’s workflows, tools, security needs, and real operational use cases. Custom case studies and guided implementation can be built directly around your organization’s data and processes.

📧 Contact us today to schedule a customized in-house, face-to-face session:


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Agenda
Module 1: Understanding LLMs

Info: • Key components of transformer architecture
• How LLMs learn and generate language
• Strengths and limitations of LLMs
Icebreaker Activity


Module 2: Working with Pre-Trained Models

Info: • Accessing commercial & open-source models
• Prompt design & iterative prompting
• Troubleshooting inaccurate outputs
Activity


Module 3: Customization & Fine-Tuning Options

Info: • When to prompt vs. when to fine-tune
• LoRA, RAG, embeddings & vector stores
• Preparing datasets for custom behavior
Hands-On Demonstration


Module 4: Application & Integration

Info: • API workflows for product development
• Building assistants, chatbots, and automation scripts
• Connecting LLMs to private enterprise knowledge
Case Study


Module 5: Business Use Cases & ROI

Info: • Efficiency, decision support, and creativity applications
• Cost considerations and scaling strategies
• Evaluating ROI and success metrics
Activity


Module 6: Responsible & Ethical AI

Info: • Privacy, compliance, transparency, and safety
• Preventing biased or harmful output
• Governance frameworks across AU / DE / UK
Group Brainstorm Activity


Module 7: Project & Action Plan

Info: • Mini Build: Apply LLM integration to a real workflow
• Define clear next steps and implementation roadmap
Action Plan Review


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Event Venue & Nearby Stays

Regus ON, London – London City Centre, 380 Wellington Street#Tower B, 6th Floor, London, Canada

Tickets

CAD 537.42 to CAD 699.92

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