Course Positioning
Course Objectives
 
Students will be able to log in to the system independently, conduct basic AI conversations, upload documents for analysis, and master model switching and the use of prompt templates.
 
 
 
Course Structure
 
Unit 1: Entering the System and an Overview of the Environment
 
1. Connecting and Logging In
 
 
 
 
Access the AI service interface (Open WebUI) through your browser; the default port is 8080.
 
 
 
 
An explanation of the user registration and login process.
 
 
 
 
 
2. Interface Tour
 
 
 
 
Left sidebar: chat-history management and the model menu.
 
 
 
 
Bottom input box: the core area for interacting with the AI, supporting both text and document input.
 
 
 
 
Settings: personalized preferences and interface-language adjustment.
 
 
 
 
 
Unit 2: Core AI Conversation Techniques
 
1. Model Switching
 
 
 
 
Switch between different LLMs (such as Llama 3, Gemma, and GPT-OSS) with one click based on task complexity and language needs.
 
 
 
 
Understand how different models differ in processing speed and reasoning ability.
 
 
 
 
 
2. Using the Prompt Template Library
 
 
 
 
Use the "engineering-grade prompt template library"—for example, marketing-expert and event-planning templates—to improve response accuracy.
 
 
 
 
Worked example: how to quickly generate a promotional event plan using a template.
 
 
 
 
 
Unit 3: RAG Retrieval-Augmented Generation (Document Q&A)
 
1. Uploading Files
 
 
 
 
Click the "+" to the left of the input box to upload PDF, Excel, or Word files.
 
 
 
 
 
2. Targeted Document Q&A
 
 
 
 
Use the # symbol in the input box to select a specific document for the conversation.
 
 
 
 
Hands-on practice: enter "Please summarize the key points of this PDF report" and tag the file.
 
 
 
 
 
3. Privacy and Security
 
 
 
 
Understand the advantages of on-premises data processing and ensure that core intellectual property (financial reports, contracts, etc.) never leaks to third-party servers.
 
 
 
 
 
Unit 4: Advanced Features and Collaboration
 
1. Search and Information Retrieval
 
 
 
Use connectivity features (such as Jina Fetch) to automatically compile market intelligence or monitor competitors' activity.
 
 
 
 
2. Conversation Management and Export
 
 
 
 
Write conversation data into a form or save it to Google Sheets.
 
 
 
 
Knowledge retention: keep great prompts and interaction experience within the organization to prevent the loss of assets.
 
 
 
 
 
Course Highlights
 
✅ Fully private on-premises implementation
 
✅ Engineering-grade prompt library applications
 
✅ A hands-on, RAG-focused approach
 
✅ Cross-tool collaboration and integration
 
 
 
Learning Outcomes
 
 
 
Independently control the AI interface
 
 
Gain effective questioning skills
 
 
Realize "documents as knowledge"
 
 
Master a new path for information retrieval
 
 
Build information-security awareness
 
 
 
 
Who Should Attend
 
 
 
 
Administrative and marketing staff: for copywriting and data compilation.
 
 
 
 
Product R&D teams: for spec-sheet analysis and finding technical documents.
 
 
 
 
Senior managers: for quickly grasping large volumes of financial reports or market-trend reports.