Course topics include:
Mastering the operating principles and model limitations of LLM
Optimizing AI responses using prompt engineering
Applying the Chain of Thought (CoT) to handle complex logic
Building a RAG knowledge base for precise file citation
Develop AI Agents with Autonomous Reasoning Capabilities
Embedding Python code to connect to external APIs
Release a dedicated AI web application
LLM Principles and Intelligent Assistant Development
By mastering the operational mechanism of large-scale language models and utilizing a visualization platform to quickly configure AI Personas, we can build the first dedicated intelligent dialogue assistant.
Advanced Prompt Engineering
By deeply learning Zero-shot and CoT (CoT) technologies, we can guide the model logic with precise instructions, significantly improving the quality and stability of AI responses.
Practical RAG Knowledge Base Architecture
By using Retrieval Augmentation Generation (RAG) technology, school manuals or textbooks can be transformed into vector data, creating an AI that can "understand" documents and provide accurate answers.
Automated Workflow Design
Learn the system architecture logic, apply conditional branches (If/Else) and intent recognition nodes, and design intelligent processes that can automatically triage and process complex tasks.
AI Agents and Networking Tools
Develop agents with autonomous reasoning capabilities and integrate them with online tools such as Google Search, enabling AI to proactively plan steps and acquire the latest information.
Python integration and API connection
Advanced features include embedding Python code nodes for data processing and connecting to external APIs (such as weather data), infinitely expanding the functional boundaries of AI systems.
Project Launch and Web App Deployment
By integrating the front-end interface design and back-end logic, the developed AI Agent is published as a standalone Web App for real users to use.
Python Basics Course
Without prior Python knowledge, learning the LLM course directly may be challenging. This course series requires a certain level of Python programming skills.
If students are interested in LLM courses but lack Python experience, it is recommended that they first take the ICT Python course to build a solid programming foundation. The ICT Python course can help students systematically learn Python syntax and programming concepts.
FAQ
AI technology trivia
LLM (Large Language Model) These are AI models based on deep learning, such as GPT-4 or Claude. Unlike traditional, mechanical chatbots that rely on keyword matching, LLMs possess the ability to understand context, reason, and generate content. This course will teach students how to master these models, elevating them from mere "users" to "developers."
AI Agent (Intelligent Agent) This is considered the next stage of generative AI. Ordinary AI (like ChatGPT) can only passively answer questions; while AI agents possess… "Perception, Planning, Action" It possesses the ability to autonomously search for the latest information online, use tools (such as computers and APIs), and perform complex tasks. Learning to develop AI agents is equivalent to mastering the core of future automation technology.
RAG (Retrieval-Augmented Generation) It's a technology that allows AI to "understand" specific knowledge bases. General AI might fabricate facts (hallucinations); through RAG technology, we can input "school manuals" or "subject textbooks" into AI, allowing it to provide accurate answers based on facts. This is how to build... School-based AI teaching assistant or Intelligent Customer Service Key technologies.
unnecessary. This course uses advanced... Visual Orchestration Platform The teaching method focuses on designing AI workflows primarily through logic modules (Nodes), significantly lowering the barrier to entry for coding. We start with basic Prompt Engineering, enabling even junior high school students to develop enterprise-level AI applications.
Completely consistent. This course covers Artificial Intelligence (AI) and Large Language Models (LLM) This course falls within the designated technology categories for funding. The curriculum includes AI theory, system architecture design, and practical application development, aiming to enhance students' IT literacy and innovation capabilities, fully meeting the funding program's approval criteria. We can provide a detailed project proposal template to assist schools with their applications.
unnecessary. The ones we chose Enterprise-level AI development platform Supporting cloud-based deployment, schools can run powerful LLM models without purchasing expensive GPU servers. Students can develop and test using only a regular computer or tablet through a browser, greatly reducing the hardware barrier.
Students will complete a [participant's task] at the end of the course. A dedicated AI Web AppThis could be a "campus information query assistant," a "subject-specific intelligent tutor," or an "automated research agent." This web app can generate unique URLs that can be shared with teachers or classmates, enriching students' lives. OLE orICT SBAwork.
Request the full course syllabus
Get Vinci AI by filling out the form once. Complete course resource library Cloud access permissions. We have prepared the following documents for your convenience. Curriculum Planning and IT Innovation Lab / QEF Grant Application
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📘 Course Unit Structure: Coverage Python LLM,AI-generated art, Unitree robotics courses, etc.syllabus
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🤖 Hardware specifications: Unitree Robots (Go2, R1),drone swarm and UGOT Robot Hardware Details
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🏆 Activity plan reference: STEM Day: Comprehensive Learning Day Procedures and School Competition Details
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Trusted by top universities and government agencies
AI online course co-development partner
Online professional development training was organized for all teachers in Hong Kong, with over 500 teachers participating; exclusive online self-study courses and workshops on AI and computational thinking were developed, with over 10,000 students enrolled.
AI Application Practice Partner (Office of the Chief Information Officer)
For two consecutive academic years, we have collaborated with the Office of the Director of Information Technology at the Education University of Hong Kong to conduct AI training for the university's faculty and staff, covering topics such as report generation and academic surveys.
Training for 2,000+ AI Innovation Talents
A large-scale AI training camp was held for over 2,000 students across the university, focusing on how to apply generative AI tools to optimize project design and creative brainstorming.
Exclusive AI Training Partner (Serving 9,000 Faculty and Staff)
Developed a one-stop online AI skills training platform for the University of Hong Kong, serving over 9,000 faculty and staff users; provided all faculty and staff with tiered self-study videos and offline practical workshops, covering a comprehensive range of courses from basic principles to advanced applications.
AI Higher Education Training Commissioning Institution
We were commissioned to create a series of training programs for their faculty and staff on "The Application and Teaching Practice of AI in Higher Education"; guiding teachers to integrate AI into curriculum design, teaching assessment and student counseling.
Upgrading administrative and teaching effectiveness
This course provides HKUST faculty and staff with in-depth AI data analytics instruction, teaching them how to use AI to quickly process complex university data and extract insights from it.
AI artificial intelligence courses for primary and secondary schools
Our strength lies in our course team, which consists of university lecturers and AI experts with doctoral degrees, and each instructor holds the Jetson AI Ambassador certification issued by NVIDIA. NVIDIA is a global leader in visual computing technology, focusing on artificial intelligence and edge computing. Its Jetson platform has become an essential tool for AI research and development worldwide. The Jetson AI Ambassador certification is specifically designed for educators, which means our instructors not only possess profound AI and Jetson knowledge but have also undergone rigorous evaluation by NVIDIA to demonstrate their ability to teach AI and Jetson effectively.
