|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/avoiding-failure-in-ai-projects/
课程评论：没有评论
课程名称：避免人工智能项目失败 课程概述：随着数据价值的不断提升以及机器学习和人工智能潜力的日益被认识，组织迫切希望利用这些技术。然而，令人震惊的是，约有87%的AI项目未能投入生产，这突显了采用系统性方法以避免陷阱、做出明智职业决策的必要性。本课程旨在提高对AI项目常见陷阱的认识，并提供战略性指导，以降低失败风险并增强用户参与感。课程涵盖有效AI项目管理的基本策略，包括项目启动、获取业务/流程理解和高效部署AI解决方案。 参与者将学习明确项目目标和交付成果的重要性、领域知识的整合，以及与利益相关者之间的沟通与合作。课程还提供了关于最终用户参与、量化项目成功以及运用失效模式与效果分析（FMEA）和chatGPT进行风险评估与缓解的实用见解。虽然本课程不直接教授编程或机器学习等技术技能，但建议具有一定数据分析、数据管理或IT职位技术背景的个人参加。 通过本课程，参与者将获得宝贵的知识和实用工具，以降低失败风险、增强用户参与，并在项目生命周期内做出明智决策。本课程为学习者提供了将AI项目转变为成功项目的策略，使其与商业目标相一致并带来可观收益。掌握这一新知识后，参与者能够在动态数据科学领域提升项目和团队的表现。
With the growing recognition of data's value and the potential of machine learning and artificial intelligence, organizations are eager to leverage these technologies. However, a staggering 87% of AI projects fail to make it into production, highlighting the need for a systematic approach to avoid pitfalls and make informed career decisions. This course aims to increase awareness about the most common pitfalls of AI projects and provide a strategic guideline to reduce the risk of failure and enhance user-engagement. The course covers essential strategies for effective AI project management, including project kick-off, obtaining business/process understanding, and efficient deployment of AI solutions. Participants will learn about the importance of clear project goals and deliverables, domain knowledge integration, and communication and collaboration with stakeholders. Practical insights on end-user engagement, quantifying project success, and applying Failure Mode and Effect Analysis (FMEA) and chatGPT for risk assessment and mitigation are also provided.While the course does not directly teach technical skills like programming or machine learning, it is recommended for individuals with a certain level of technical knowledge in data analytics, data management, or IT positions.By the end of the course, participants will have gained valuable knowledge and practical tools to reduce the risk of failure, enhance user engagement, and make informed decisions throughout the project lifecycle. The course equips learners with strategies to transform AI projects into successful endeavors that align with business objectives and deliver tangible benefits. With this newfound expertise, participants can take their projects and teams to the next level in the dynamic landscape of data science.
