|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/product-focused-ai/
课程评论：没有评论
课程名称：从猫狗项目学习机器学习产品管理 这是一个为期30天无风险退款的课程，旨在用最少的时间（仅2.5小时）高效地教授构建AI产品所需的最高影响力概念和策略。 **课程亮点：** 1. **机器学习基础：** 课程使用可爱的猫狗图片和由受过训练的教育心理学家设计的练习，轻松解释机器学习的基本概念、用例和关键成功指标。避免复杂的数学公式和算法，聚焦核心概念。 2. **深度学习实操（无需编程）：** 提供一个预先构建好的代码笔记本，利用深度学习来预测图片是猫还是狗。通过简单的练习巩固机器学习概念，无需实际编写任何代码。 3. **用户体验与研究：** 学习如何最大化AI项目的用户体验设计，并在产品开发的各个阶段有效地降低产品想法的风险。 4. **与ML工程师的有效沟通：** 掌握与机器学习工程师沟通项目时应提出的关键问题，涵盖业务目标、数据获取、权衡、资源和风险等方面。 5. **机器学习项目产品路线图：** 提供一个现成的产品路线图模板，用于规划机器学习项目。 6. **互动讨论与实践：** 通过有趣的讨论板练习，巩固课程内容，并与其他学习者交流创意，例如：思考ML用例、绘制数据科学循环图、定义项目成功指标、考虑UX、制定研究路线图、创建产品路线图和UX模型等。 7. **用户研究方法选择：** 提供用户研究路线图和图表，帮助您为项目选择最佳的研究方法。 **先决条件：** 您需要一个Google账户来访问Google Classroom和使用Google Colab在线编程笔记本。
This 30 day money back guarantee course is optimized to teach you the highest impact concepts and strategies for building an A.I. product in the least time possible, just 2.5 hours, with no risk! Your time is valuable don't waste it on a longer, less efficient course, take this one to quickly learn: 1)The basics of machine learning, use cases and major success metrics easily explained using concrete examples of cute dogs and cats and exercises designed by a trained educational psychologist. No unnecessary or confusing math equations or algorithms, just the core concepts!2)A pre-made coding notebook for predicting if an image is a cat or dog with deep learning with simple exercises to reinforce ML concepts that teach you the fundamental concepts without having to learn any code whatsoever!3)User experience and user research tips to maximize the design of your potential A.I. project and efficiently de-risk your product ideas at many stages of development!4)The best questions to ask your ML engineer when sizing and planning a project about business goals, data acquisition, tradeoffs, resources and risk!5)A handy product roadmap for scoping out your machine learning project.6)Fun discussion board exercises to help reinforce concepts throughout the course and see what other students are creating such as: thinking about ML use cases, mapping out the data science loop for your project, success metrics for your project, UX considerations, making a research roadmap for your project, making a product roadmap and UX mockup for your project.7)A user research roadmap and chart to help you select the best methods to research your project.Please note: for this course you will need a google account to access google classroom and to utilize google collab coding notebooks!
