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所在平台: Udemy |
课程主页: https://www.udemy.com/course/generative-ai-for-transportation-analyst-and-managers/
课程评论：没有评论
课程名称：交通分析师和经理的生成性人工智能 课程概述：本综合课程旨在为交通分析师和物流经理提供利用生成性人工智能（Generative AI）实现战略和运营卓越的技能。课程起始于对“什么是生成性人工智能”和“提示工程（Prompt Engineering）”等概念的深入理解，学习者将探讨大型语言模型（LLM）如何彻底改变运输工作流程。 课程内容包括：深入学习零-shot、one-shot和few-shot提示技术，参与者将学习如何为不同的物流场景定制AI响应。实践应用方面，包括从实时货物约束生成最佳配送路线，利用交通和天气提示动态调整路线，以及使用AI洞察选择枢纽位置和运输模式。此外，学习者还将掌握车辆装载计划、容量利用率和自动承运商绩效报告的技巧。课程还涵盖了针对货运投标、投标文件以及合同条款比较的AI支持，采用先进的提示方法。 参与者将练习自动生成海关表格、提单、托运单和运单，简化文档工作流。附加模块指导用户制定仓储和运输的标准操作程序（SOP）、生成实时预计到达（ETA）预测，以及建立路线偏离的警报系统。课程还探讨了如何将生成性AI应用于模拟运输需求、预测季节性和地区能力，并对比历史和预期的运输量。学生将生成绩效KPI，识别闲置时间和停机时间，并使用AI技术分析交货时间和SLA违约。 高级部分包括基于风险的干扰规划、紧急响应模板，以及受外部信号（如新闻和天气）驱动的模拟。课程的结尾提供了超过1000个用于实际运输决策的即时提示库，助力现代物流专业人士将AI技术与运输战略相结合，确保参与者能够引领其组织进入一个数据驱动的智能供应链操作新时代。
This comprehensive course equips transportation analysts and logistics managers with the skills to harness Generative AI for strategic and operational excellence. Beginning with a strong foundation in concepts such as "What is Generative AI" and "Prompt Engineering," learners will explore how Large Language Models (LLMs) can revolutionize transportation workflows. Through a deep dive into zero-shot, one-shot, and few-shot prompting techniques, participants learn to tailor AI responses for diverse logistics scenarios. The course progresses to practical applications including generating optimal delivery routes from real-time shipment constraints, adjusting routes dynamically using traffic and weather prompts, and selecting hub locations and transport modes using AI insights.Further, learners gain expertise in vehicle load planning, capacity utilization, and automated carrier performance reporting. AI-driven support for freight tendering, bidding documents, and contract clause comparisons is covered using advanced prompting methods. Participants will also practice generating customs forms, bills of lading, consignment notes, and waybills automatically, streamlining documentation workflows. Additional modules guide users through drafting SOPs for warehousing and shipping, generating real-time ETA predictions, and building alert systems for route deviations.The course explores how Generative AI can be applied to simulate transport demand, forecast seasonal and regional capacity, and compare historical versus projected volumes. Students will generate performance KPIs, identify idle time and downtime, and analyze lead times and SLA breaches with AI-powered precision. Advanced sections include risk-based disruption planning, emergency response templates, and simulations driven by external signals like news and weather. The course culminates in a powerful library of 1000+ ready-to-use prompts for real-world transportation decision-making.Designed for modern logistics professionals, this course bridges AI technology with transportation strategy, ensuring participants can lead their organizations through a new era of data-driven, intelligent supply chain operations.
