This hands-on master class is designed for non-technical managers and business leaders in multinational companies. The program focuses on building practical skills to install, run, and use LLMs directly on your own computer. By working with AI locally, you can safely analyze sensitive documents, extract insights, and automate workflows without exposing confidential information to cloud services.

The program is delivered as an in-person workshop in Shanghai, combining expert instruction, hands-on setup, and practical exercises. Participants work directly on their own computers to install models, run AI-powered analyses, and build small local automations. They leave with a personalized on-device AI workflow, a secure local AI environment, and actionable methods they can apply immediately, along with the confidence to lead responsible, cost-effective AI adoption within their teams.

• Benefits of on-device AI: security, compliance, sovereignty, and low latency
• Differences between cloud AI and local AI for company data
• Installing inference engines and local open-source LLMs on Mac and Windows
• Building secure, offline workflows for data analysis and daily productivity
• Automating tasks by connecting local files, folders, and desktop tools
• Defining guardrails, permissions, and internal governance for on-device AI use

Module 1: On-Device AI Foundations

Why on-device AI matters

· Compare cloud AI versus on-device (local) AI

· Understand security, data sovereignty and compliance constraints

· Identify latency, cost, and availability benefits

On-device AI use cases

· Analyze sensitive company documents offline

· Experiment safely with proprietary datasets

· Support daily manager tasks without data leakage

Module 2: Setting Up Local AI on Your Computer

Installing inference environments

· Prepare system requirements for local AI

· Install inference engines on Mac / Windows systems

· Verify performance and hardware compatibility

Running local open-source models

· Download and manage local LLM models

· Select models by size and task type

· Start, stop, and switch models locally

· Monitor resource usage and performance

Module 3: Working with Company Data Offline

Secure document analysis workflows

· Analyze Excel, PDF, and Word documents

· Summarize reports into executive takeaways

· Extract insights from internal presentations

· Compare multiple documents securely offline

Module 4: Local Automations and Desktop Integration

File and folder automation

· Connect AI to local file systems

· Batch process documents in folders

· Auto-rename, summarize, and classify files

· Trigger workflows from file changes

Task and tool integration

· Link AI outputs to task lists

· Automate follow-up and reminders locally

· Connect AI with desktop productivity tools

· Build simple background automations

Module 5: Governance, Guardrails, and Team Adoption

Defining safe usage rules

· Classify data by sensitivity levels

· Define approved on-device AI use cases

· Set rules for model and data access

· Establish escalation for sensitive requests