Course Code: llmsforacs
Duration: 14 hours
Prerequisites:
  • 瞭解基本程式設計概念
  • 建議有 Python 程式設計經驗,但不是必需的。
  • 熟悉基本的機器學習概念是有益的

觀眾

  • 客戶支援專業人員
  • IT 專業人員
  • Business 分析師
Overview:

Large Language Models (LLMs) 是一種處理和生成類似人類文本的人工智慧,可實現更自然、更有效的自動化客戶支援。

這種以講師為主導的現場培訓(在線或現場)面向希望實施 LLM 以創建回應迅速且智慧的客戶支援聊天機器人的初級到中級客戶支援和 IT 專業人員。

在培訓結束時,參與者將能夠:

  • 瞭解 Large Language Models (LLMs) 的基礎知識和架構。
  • 設計 LLM 並將其整合到客戶支援系統中。
  • 增強聊天機器人的回應能力和用戶體驗。
  • 解決道德考慮並確保符合行業標準。
  • 為實際應用程式部署和維護基於 LLM 的聊天機器人。

課程形式

  • 互動講座和討論。
  • 大量的練習和練習。
  • 在現場實驗室環境中動手實施。

課程自定義選項

  • 如需申請本課程的定製培訓,請聯繫我們進行安排。
Course Outline:

Large Language Models (LLMs) 簡介

  • 客戶支援中的 AI 概述
  • LLM的基礎
  • 聊天機器人的演變:從簡單的腳本到人工智慧驅動的支援

LLM的架構

  • 瞭解 LLM 的構建塊
  • LLM 中的神經網路和深度學習
  • 訓練 LLM:數據、演算法和計算資源

在聊天機器人中實現 LLM

  • 現有系統中 LLM 的整合策略
  • 設計對話流和使用者交互
  • 確保上下文理解和連貫性

增強聊天機器人的回應能力

  • 即時回應生成技術
  • 處理併發對話
  • 個人化和預測性支援

用戶體驗和介面設計

  • 製作使用者友好的聊天機器人介面
  • 視覺和文本提示,提高參與度
  • 反饋迴圈和持續改進

道德考量與合規

  • LLM 的隱私和數據安全
  • 在客戶支援中合乎道德地使用人工智慧
  • 遵守行業標準和法規

測試和部署

  • 質量保證和測試方法
  • 可伸縮性和可靠性的部署策略
  • 聊天機器人系統的監控和維護

案例研究和實際應用

  • 分析 LLM 聊天機器人的成功實施
  • 經驗教訓和最佳做法
  • 人工智慧驅動的客戶支持的未來趨勢和創新

專案與評估

  • 設計和構建基於 LLM 的聊天機器人
  • 同行評審和小組討論
  • 最終評估和反饋

摘要和後續步驟

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