AI Application Development and Practice System

The AI Application Development and Practice Platform supports seven application modules that are both independent and interconnected. The platform follows a progressive learning path: "Cognitive Foundation → Building Processes → Strengthening Interaction → Moving Towards Agents → Application Scenarios." Each module focuses on a key AI technology, providing practical experience through specific service industry scenarios (e.g., hospitality, tourism, study tours, etc.). Platform functionalities cover GenAI principles, advanced Prompt design, design of different types of workflows, Chatbot dialogue flow management, Agent tool calling, behavior modeling, and more, helping students systematically master core capabilities from foundational knowledge to practical application.

Core Functions

  • Cultivating Scene-Based AI Problem-Solving Skills: The platform facilitates practical training driven by real-world service industry scenarios such as hotels and tourism. This helps users master how to identify business pain points and utilize a GenAI mindset to construct feasible AI solutions.
  • Intelligent System Interaction and Evaluation: The platform provides practical modules for intelligent systems like Chatbots and Agents. Users can experience immersive interaction with these systems and learn how to critically evaluate AI outputs, identify issues, and propose optimization suggestions.
  • AI Workflow and Agent Construction: The platform covers the full technical chain from Prompt design to Agent tool calling and behavior modeling. It guides users to understand complex task decomposition and Agent execution mechanisms, mastering the ability to design different types of AI workflows and construct agents.
  • GenAI Core Technologies and Practical Application: The platform adopts a spiral progression design, systematically explaining GenAI principles and working mechanisms. Through practical sessions, it helps users understand and master the specific applications and implementation methods of GenAI in service industry scenarios.
  • Data Processing and Analysis Practice: The platform supports the processing of common structured and unstructured data in the service industry and provides corresponding tools and processes. This enables learners to practice as they learn, mastering key skills in information extraction and analysis.
  • Strengthening Systems Thinking and Innovative Practice: Through an integrated practice model of knowledge and action and a capability-oriented training philosophy, the platform focuses on enhancing users' systems thinking abilities and encourages innovative application of AI in real-world contexts.
  • Fostering Awareness of Responsible AI Application: During the practical process, the platform incorporates discussions on ethical issues such as data security, privacy protection, and bias identification, guiding users to establish an awareness of responsible AI application.

Application Principles

  • Modular Learning: The platform breaks down the complex AI application development process into seven distinct yet interconnected application modules. Each module focuses on a key technical aspect of AI, such as GenAI principles, Prompt design, or Chatbot management. This approach ensures a structured and targeted learning experience.

  • Spiral Progression: The platform follows a progressive learning path: "Cognitive Foundation → Process Construction → Interaction Reinforcement → Moving Towards Agents → Application Scenarios." This means learners will revisit core concepts repeatedly, but each time they'll practice in deeper and more complex application scenarios, gradually solidifying their understanding and mastery.

  • Large Model Technology Integration: At its core, the platform utilizes Generative AI (GenAI), leveraging the powerful capabilities of Large Language Models (LLMs) to support the development and execution of intelligent agents. Through prompt engineering, agent tool invocation, and behavioral modeling, the platform enables AI to make intelligent decisions and interact within specific service industry scenarios.

  • Data Processing and Analysis: The platform supports the processing of both structured and unstructured data, allowing AI systems to extract and analyze information from various sources. This provides data-driven solutions for the hotel and tourism industry.

  • Human-Computer Interaction Design: Features such as Chatbot dialogue flow management are integrated into the platform, emphasizing the intelligent system's ability to interact with users. By designing and optimizing dialogue processes, the platform enhances user experience and facilitates more natural and efficient human-computer collaboration.

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