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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-product-management-grow-your-career/
课程评论：没有评论
课程名称：《人工智能产品框架：自信构建与拓展》 课程概述：通过全面探索基础原则、实用框架和实践活动，学习者将掌握开发和管理与商业目标相一致的人工智能驱动产品的专业知识，并实现可衡量的成果。 模块1：人工智能产品框架简介 涵盖内容：人工智能产品框架的定义、人工智能产品管理与传统产品管理的区别、人工智能产品经理的关键责任、技能与能力。 主要收获：理解创建模型驱动产品的框架，确定人工智能产品经理为组织带来的独特价值。 模块2：采用产品运营模型 涵盖内容：产品运营模型概述、产品经理、数据科学家、技术负责人和产品领导的角色、如何围绕价值、可用性、可行性和生存性组织团队。 主要收获：学习如何利用产品运营模型交付可衡量的结果。 模块3：人工智能产品基础 涵盖内容：人工智能分支概述（例如：机器学习、自然语言处理、计算机视觉、生成式人工智能）、人工智能算法和工作流程的运作、有效管理人工智能产品。 主要收获：建立人工智能概念和应用的基础理解。 模块4：人工智能产品战略 涵盖内容：人工智能产品战略的原则：专注、数据驱动洞察、透明度和下注、如何将人工智能目标与商业目标对齐。 主要收获：发展战略思维，识别和优先解决高影响问题。 模块5：人工智能产品发现 涵盖内容：验证问题、评估风险和快速实验、发现原则：最小化浪费、评估风险和验证解决方案。 主要收获：理解产品发现确保解决方案在价值、可用性、可行性和生存性方面的有效性。 模块6：人工智能产品交付与ML运维 涵盖内容：人工智能产品交付中的持续集成/持续交付（CI/CD）和迭代开发、机器学习运维生命周期：开发、部署、监控与再训练。 主要收获：学习如何确保人工智能解决方案的可靠性、可扩展性和适应性。 模块7：在人工智能领域发展你的职业 涵盖内容：在人工智能方面建立专业知识、领导人工智能产品框架和伦理人工智能实践、持续学习和跟进最新动态的战略。 主要收获：制定人工智能产品管理职业发展的路线图。 模块8：主要收获与课程项目 涵盖内容：课程模块和框架总结、人工智能产品框架的实际应用。 主要收获：将关键学习综合成一个可展示的课程项目。 课程项目：设计一个电子商务平台的推荐系统，重点关注战略、发现和交付阶段，创建最终演示文稿总结你的发现、解决方案和成果。 学习成果：完成本课程后，参与者将能够理解人工智能产品管理的独特方面及其与传统产品管理的区别，应用产品运营模型组织团队和实现成果，发展与商业目标对齐的人工智能产品战略，执行发现流程以验证问题并识别有效解决方案，利用CI/CD原则和ML运维框架交付和管理人工智能产品，在人工智能产品管理领域建立领导力和专业知识，推动事业发展。 课程物流： • 时长：8个模块 • 授课方式：在线，自主学习 • 完成证书：完成所有活动及最终项目后颁发证书。
Through a comprehensive exploration of foundational principles, practical frameworks, and hands-on activities, learners will gain expertise in developing and managing AI-driven products that align with business goals and deliver measurable outcomes.Module 1: Introduction to the AI Product FrameworkTopics Covered:What is the AI Product Framework?How AI Product Management differs from traditional Product Management.Key responsibilities, skills, and competencies of AI Product Managers.Key Takeaways:Understand the framework for creating model-driven products.Identify the unique value AI Product Managers bring to organizations.Module 2: Adopting the Product Operating ModelTopics Covered:Overview of the Product Operating Model.Roles of Product Managers, Data Scientists, Tech Leads, and Product Leadership.How to organize teams around value, usability, feasibility, and viability.Key Takeaways:Learn how to deliver measurable outcomes using the Product Operating Model.Module 3: Foundations of AI ProductsTopics Covered:Overview of AI branches (e.g., machine learning, NLP, vision, generative AI).How AI algorithms and workflows function.Managing AI products effectively.Key Takeaways:Build a foundational understanding of AI concepts and applications.Module 4: AI Product StrategyTopics Covered:Principles of AI Product Strategy: Focus, Data-Driven Insights, Transparency, and Placing Bets.How to align AI goals with business objectives.Key Takeaways:Develop strategic thinking to identify and prioritize high-impact problems.Module 5: AI Product DiscoveryTopics Covered:Validating problems, assessing risks, and rapid experimentation.Principles of discovery: minimize waste, assess risks, and validate solutions.Key Takeaways:Understand how product discovery ensures solutions are valuable, usable, feasible, and viable.Module 6: AI Product Delivery & ML OpsTopics Covered:CI/CD and iterative development in AI product delivery.ML Ops lifecycle: Development, Deployment, Monitoring, and Retraining.Key Takeaways:Learn how to ensure reliability, scalability, and adaptability of AI solutions.Module 7: Growing Your Career in AITopics Covered:Building expertise in AILeadership in the AI Product Framework and ethical AI practices.Strategies for continuous learning and staying updated.Key Takeaways:Develop a roadmap for career advancement in AI Product Management.Module 8: Key Takeaways & Course ProjectTopics Covered:Summary of course modules and frameworks.Real-world application of the AI Product Framework.Key Takeaways:Synthesize key learnings into a portfolio-ready course project.Course Project: Design a recommendation system for an e-commerce platform, focusing on strategy, discovery, and delivery phases. Create a final presentation summarizing your findings, solutions, and outcomes.Learning OutcomesBy the end of this course, participants will:Understand the unique aspects of AI Product Management and its differences from traditional Product Management.Apply the Product Operating Model to organize teams and achieve outcomes.Develop AI product strategies that align with business goals. Execute discovery processes to validate problems and identify effective solutions.Deliver and manage AI products using CI/CD principles and ML Ops frameworks.Build leadership and expertise in AI Product Management to grow their careers.Course Logistics• Duration: 8 Modules• Delivery Mode: Online, self-paced• Certificate of Completion: Awarded upon successful completion of all activities and the final project.
