課程簡介
混合AI-量子系統簡介
- 量子計算原理概述
- 混合AI-量子系統的關鍵組件
- 量子AI在各行業的應用
量子機器學習算法
- 量子機器學習算法:QML、變分算法
- 使用量子處理器訓練AI模型
- 經典AI與量子AI方法的比較
混合AI-量子系統的挑戰
- 處理量子系統中的噪聲和糾錯
- 可擴展性和性能限制
- 確保與經典AI框架的集成
量子AI的實際應用
- 混合AI-量子系統在行業中的案例研究
- 量子計算平臺的實踐應用
- 探索量子AI的潛在突破
優化量子AI工作流程
- 管理混合經典-量子工作流程
- 最大化量子AI系統的資源利用率
- 量子AI與經典AI基礎設施的集成
混合AI-量子系統的特定用例
- 量子AI在優化問題中的應用
- 藥物發現、金融和物流中的用例
- 量子增強的強化學習
AI與量子計算的未來趨勢
- 量子硬件和軟件的進展
- 量子AI在各個領域的未來潛力
- 量子AI研究與發展的機遇
總結與下一步
最低要求
- 深入瞭解AI和機器學習
- 熟悉量子計算原理
- 具備算法開發和模型訓練的經驗
受衆
- AI研究員
- 量子計算專家
- 數據科學家和機器學習工程師
客戶評論 (1)
Quantum computing algorithms and related theoretical background know-how of the trainer is excellent. Especially I'd like to emphasize his ability to detect exactly when I was struggling with the material presented, and he provided time&support for me to really understand the topic - that was great and very beneficial! Virtual setup with Zoom worked out very well, as well as arrangements regarding training sessions and breaks sequences. It was a lot of material/theory to cover in "only" 2 days, wo the trainer had nicely adjusted the amount according to the progress related to my understanding of the topics. Maybe planning 3 days for absolute beginners would be better to cover all the material and content outlined in the agenda. I very much liked the flexibility of the trainer to answer my specific questions to the training topics, even additionally coming back after the breaks with more explanation in case neccessary. Big thank you again for the sessions! Well done!