Devseis

Enable professionals with basic computer skills to install, configure, and use local LLMs AI agents for data analysis, document processing, and decision-making—without sending data to the internet.
Enable executives to run AI locally without sending sensitive data to the cloud.
Simplify LLM deployment for beginners (no coding required).
Teach secure, offline AI workflows for document analysis, spreadsheets, and automation.
Compare local vs. cloud AI – When to use each.
Ensure data sovereignty for GDPR and corporate compliance.

Module 1: Why Local AI? Privacy, Security & Business Benefits What you’ll learn: – Risks of cloud-based AI (data leaks, compliance issues) – Advantages of local AI (GDPR-friendly, full control, no vendor lock-in) – Use cases: Document analysis, internal data Q&A, report generation Demo: – A local AI chatbot answering questions from an internal PDF
Module 2: Understanding Local LLMs – No Technical Jargon What you’ll learn: – What is an LLM? (Simplified for non-tech users) – Open-source vs. proprietary models (Mistral, Llama 3, Phi-3 vs. ChatGPT) – Hardware requirements (Do you need a GPU? Can a laptop handle it?) Exercise: – Checking your computer’s specs for AI compatibility
Module 3: Installing Your First Local AI – Step-by-Step Guide Tool of choice: Ollama (user-friendly local LLM manager) Alternative: LM Studio (for Windows/Mac with GUI) Hands-on: – Installing & running a small LLM (eg, Mistral 7B) – Troubleshooting: Common installation issues & fixes
Module 4: Interacting with Your Local AI – Chat & Basic Prompts What you’ll learn: – How to “talk” to your AI (basic prompting for business use) – Asking for summaries, insights, and data extractions Workshop: – Uploading a PDF (eg, a financial report) and querying it
Module 5: Local AI for Data Analysis – Spreadsheets & Databases What you’ll learn: – Using local AI to analyze CSV/Excel files (no Python needed) – Tool: Pandas AI (local mode) or LibreChat (for structured queries) Exercise: – Uploading sales data and asking, “What are the top 3 trends?”
Module 6: AI Agents for Automation – Simple Workflows What you’ll learn: – What is an AI agent? (AutoGPT, BabyAGI simplified) – Use case: Automating meeting notes, email sorting Demo: – A local AI agent scanning a folder of docs and generating a summary
Module 7: Security & Maintenance – Keeping Your AI Safe What you’ll learn: – Best practices for data isolation (firewalls, encrypted drives) – Updating models & software – When NOT to use local AI (limitations vs. cloud AI)
Module 8: Wrap-up, Certification & Next Steps What you’ll learn: – Recap of key tools & workflows – Q&A + Real-world troubleshooting – Certification Award & Resource Kit (cheat sheets, recommended models) – Feedback & Networking

Privacy risks of cloud AI – Why local models are safer for sensitive data.
Hardware requirements – What specs are needed to run AI locally.
No-code local AI tools (Ollama, LM Studio, LibreChat).
Use cases – Internal report generation, confidential document analysis.
Security best practices – Keeping local AI models updated and isolated.

Local AI for Executives – Private, Secure, and Offline AI Analytics

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Content

Points Covered

Ready to Upskill Your Team?

Devseis