Course Code: llmsforacs
Duration: 14 hours
Prerequisites:
  • 了解基本编程概念
  • 建议有 Python 编程经验,但不是必需的。
  • 熟悉基本的机器学习概念是有益的

观众

  • 客户支持专业人员
  • IT 专业人员
  • Business 分析师
Overview:

Large Language Models (LLMs) 是一种处理和生成类似人类文本的人工智能,可实现更自然、更有效的自动化客户支持。

这种以讲师为主导的现场培训(在线或现场)面向希望实施 LLM 以创建响应迅速且智能的客户支持聊天机器人的初级到中级客户支持和 IT 专业人员。

在培训结束时,参与者将能够:

  • 了解 Large Language Models (LLMs) 的基础知识和架构。
  • 设计 LLM 并将其集成到客户支持系统中。
  • 增强聊天机器人的响应能力和用户体验。
  • 解决道德考虑并确保符合行业标准。
  • 为实际应用程序部署和维护基于 LLM 的聊天机器人。

课程形式

  • 互动讲座和讨论。
  • 大量的练习和练习。
  • 在现场实验室环境中动手实施。

课程自定义选项

  • 如需申请本课程的定制培训,请联系我们进行安排。
Course Outline:

Large Language Models (LLMs) 简介

  • 客户支持中的 AI 概述
  • LLM的基础
  • 聊天机器人的演变:从简单的脚本到人工智能驱动的支持

LLM的架构

  • 了解 LLM 的构建块
  • LLM 中的神经网络和深度学习
  • 训练 LLM:数据、算法和计算资源

在聊天机器人中实现 LLM

  • 现有系统中 LLM 的集成策略
  • 设计对话流和用户交互
  • 确保上下文理解和连贯性

增强聊天机器人的响应能力

  • 实时响应生成技术
  • 处理并发对话
  • 个性化和预测性支持

用户体验和界面设计

  • 制作用户友好的聊天机器人界面
  • 视觉和文本提示,提高参与度
  • 反馈循环和持续改进

道德考量与合规

  • LLM 的隐私和数据安全
  • 在客户支持中合乎道德地使用人工智能
  • 遵守行业标准和法规

测试和部署

  • 质量保证和测试方法
  • 可伸缩性和可靠性的部署策略
  • 聊天机器人系统的监控和维护

案例研究和实际应用

  • 分析 LLM 聊天机器人的成功实施
  • 经验教训和最佳做法
  • 人工智能驱动的客户支持的未来趋势和创新

项目与评估

  • 设计和构建基于 LLM 的聊天机器人
  • 同行评审和小组讨论
  • 最终评估和反馈

摘要和后续步骤

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