A one-stop LLM capability-building program for enterprises, government agencies, and academic institutions.
70 units / 210 hours, covering the complete path from foundational concepts to production engineering, from applied practice to frontier research.
Ph.D. · Postdoc · Full Professor
College of Computer & Data Science
100+ Papers 5 PatentsCCF Open Source ECCAAI Granular Computing
"LLMs are not merely a technology shift — they are an organization-wide capability transformation. Only systematic training enables meaningful deployment."
Why This Course
What Sets This Program Apart
Complete System
70 units progressing through Foundations → Application → Engineering → Frontier, building cumulatively — not a patchwork of disconnected tutorials.
Scenario Coverage
22 applied units cover office work, research, teaching, legal, government, healthcare, finance, manufacturing, supply chain, and media.
Production Engineering
30 engineering units span API wrappers, RAG, Agents, production deployment, observability, and security governance — full-stack and reusable.
Expert Instructor
Taught personally by Prof. Chunmao Jiang. Active researcher with years of enterprise LLM-training experience — theory meets organizational reality.
On-Premise Deployment
Focused content on local deployment, enterprise system integration, and permission governance for air-gapped and compliance-sensitive scenarios.
Capstone Project
Every participant completes a demonstrable AI application, Agent system, or knowledge assistant — directly reusable at their institution.
Modules
Module Structure
Ⅰ
Foundations
10 units · 30 hours
Zero-background friendly. Builds systematic understanding of model principles, prompting, multimodality, RAG, Agents, safety, and on-premise deployment.
Ⅱ
Applied Practice
22 units · 66 hours
Covers office work, research, teaching, operations, legal, government, healthcare, finance, manufacturing, supply chain, and media scenarios.
Ⅲ
Engineering
30 units · 90 hours
From API integration to RAG, Agents, platform integration, production deployment, security governance, and capstone delivery. The core module.
Ⅳ
Algorithms & Frontier
8 units · 24 hours
Algorithmic depth, evaluation methods, and system optimization — enabling "understanding the principles, making informed judgments, knowing the boundaries".
Recommended Tracks
Who This Is For
Research
Researchers / Faculty
Units 01–10 · 14–19 · 31–32 · 41–50 · 63–70
Research assistance, knowledge base construction, paper processing, research Agents, and horizon-broadening.
Technical
Technical Developers
Units 01–10 · 33–62 · 63–70
Full coverage of engineering, RAG, Agents, deployment, security, and algorithm fundamentals.
Help non-technical professionals quickly build stable AI-augmented workflows.
Specialization
Agent Development Track
Units 08 · 33–42 · 51–62
Focus on RAG, MCP, Claude Code, OpenClaw, Hermes, multi-Agent orchestration, evaluation and optimization.
Full 70-unit syllabus is available in Chinese.
For an English digest or customized training proposal, please
email the instructor.
Instructor
Prof. Chunmao Jiang
Full Professor at the College of Computer and Data Science, Fujian University of Technology. Ph.D. and postdoctoral researcher whose work spans granular computing, three-way decision theory, GPU scheduling, and large language model systems.
Research Interests
Research Focus
Uncertainty in AIGranular ComputingThree-Way DecisionCompute Resource OptimizationLLM Hallucination Detection
Memberships
Academic Service
CCF (China Computer Federation) Open Source Development Committee · Executive Member
CAAI (Chinese Association for AI) Granular Computing & Knowledge Discovery Committee · Member
Experience
Training & Delivery
Delivered LLM training programs for enterprises, government agencies, and universities across China. Known for bridging theoretical depth with pragmatic organizational-rollout strategies — from architecture decisions to cost governance.
A growing showcase of real AI applications built on the principles taught in this program. Each demo is hands-on and inspectable — a reference for your own institution.
Teaching Assistance System
Integrated AI platform for attendance, quizzes, experiments, reports, and class-performance assessment.
LLM-augmented traffic-operations congestion prototype: real-time segment assessment, severity grading, and low-carbon dispatch advice, with an AI assistant explaining causes.