About this Event
Group Discounts:
Save 10% when registering 3 or more participants
Save 15% when registering 10 or more participants
About the course:
Duration: 1 Full Day (8 Hours)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs / Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, Snacks and beverages will be provided during the session
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:
• 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 Is It the Right Fit for You:
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.
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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.
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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
Event Venue & Nearby Stays
regus WA, Seattle - Plaza 600, 600 Stewart Street Suites 300 & 400, Seattle, United States
USD 524.44 to USD 686.21
