|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-product-management-for-data-science-ai-course/
课程评论：没有评论
课程名称：人工智能与数据科学产品管理课程 课程概述：您是否希望学习如何成为一名产品经理？您是否对人工智能与数据科学的产品管理感兴趣？如果您的答案是“是”，那么您来对地方了！本课程为您提供了一个独特的机会，您将有机会向在业界工作并高水平实施人工智能与数据科学的行业专家学习。讲师Danielle Thé是机器学习领域的高级产品经理，拥有管理科学硕士学位，并在Google和Deloitte Digital等科技公司积累了多年的产品经理和产品市场经理经验。 随着公司越来越多地利用大数据和人工智能，尤其是像ChatGPT和其他大型语言模型（LLMs）这样的前沿工具，组织对人工智能的采用在近几年暴增了270%。这一技术的广泛应用，引发了对能够管理人工智能和大数据项目的专业人才的需求。在这一背景下，产品经理在业务目标与数据科学家和人工智能专家的技术专长之间起着至关重要的桥梁作用。 课程为初学者友好设计，即使您对数据科学和人工智能不熟悉，或没有产品管理经验，我们将在前几章带您快速入门。首先，我们将介绍人工智能和数据的产品管理，您将学习产品经理的角色及其与项目经理的区别。 接下来，将介绍AI和数据的一些关键技术概念，让您了解数据分析与数据科学的区别、算法与AI的区别、机器学习与深度学习的定义及各种机器学习类型（有监督、无监督和强化学习）。这些基础知识将为您对当前AI和数据科学领域的全面了解打下基础。 在课程的第三部分，我们将讨论人工智能和数据的商业战略，内容包括如何判断公司何时需要使用AI、如何进行SWOT分析以及如何构建和测试假设。您将在此部分获得第一个作业——创建商业提案。 第四部分着重于AI和数据的用户体验，涵盖核心问题定位、用户研究方法、用户角色开发及AI原型设计的要点。第五部分将介绍数据管理，教您如何为项目获取数据、管理数据及与不同类型机器学习相关的数据需求。 随后，我们将全面审视AI或数据科学项目在公司的完整生命周期，包括产品开发、模型构建、性能评估及技术部署，让您获取这一过程的整体认知。在第十到第十二部分，您将学习如何管理数据科学和AI团队，以及如何提升团队成员之间的沟通，并讨论伦理、隐私和偏见等必要问题。 这门课程是一次精彩的学习旅程，旨在为您准备一条有趣的职业道路！选择成为产品经理的理由包括：薪资高（Glassdoor上报告的平均薪资为128,992美元）、职业晋升机会多以及市场对产品经理的高需求。每天将面临不同的挑战，提升现有技能。 立即订阅本课程！现在不学习这些技能，您将错失与他人区分开来的机会。别让未来的成功风险化为泡影！让我们开始共同学习吧！
Do you want to learn how to become a product manager?Are you interested in product management for AI & Data Science?If the answer is ‘yes', then you have come to the right place!This course gives you a fairly unique opportunity. You will have the chance to learn from somebody who has been in the industry and who has actually seen AI & data science implemented at the highest level.Your instructor, Danielle Thé, is a Senior Product Manager for Machine Learning with a Master's in Science of Management, and years of experience as a Product Manager, and Product Marketing Manager in the tech industry for companies like Google and Deloitte Digital.From security applications to recommendation engines, companies are increasingly leveraging big data and artificial intelligence, including cutting-edge tools like ChatGPT and other large language models (LLMs), to enhance operations and product offerings. In just the past few years, organizational adoption of AI has surged by 270%, driven by breakthroughs in natural language processing and machine learning. As businesses race to implement these technologies, there is a growing demand for skilled professionals who can manage AI and big data projects. In this context, a product manager plays a crucial role, bridging the gap between business goals and the technical expertise of data scientists and AI specialists.Organizations are looking for people like you to rise to the challenge of leading their business into this new and exciting change.The course is structured in a beginner-friendly way. Even if you are new to data science and AI or if you don't have prior product management experience, we will bring you up to speed in the first few chapters. We'll start off with an introduction to product management for AI and data. You will learn what is the role of a product manager and what is the difference between a product and a project manager.We will continue by introducing some key technological concepts for AI and data. You will learn how to distinguish between data analysis and data science, what is the difference between an algorithm and an AI, what counts as machine learning, and what counts as deep learning, and which are the different types of machine learning (supervised, unsupervised, and reinforcement learning). These first two sections of the course will provide you with the fundamentals of the field in no time and you will have a great overview of AI and data science today.Then, in section 3, we'll start talking about Business strategy for AI and Data. We will discuss when a company needs to use AI, as well as how to perform a SWOT analysis, and how to build and test a hypothesis. In this part of the course, you'll receive your first assignment - to create a business proposal.Section 4 focuses on User experience for AI & Data. We will talk about getting the core problem, user research methods, how to develop user personas, and how to approach AI prototyping. In section 5, we will talk about data management. You will learn how to source data for your projects and how this data needs to be managed. You will also acquire an idea about the type of data that you need when working with different types of machine learning.In sections 6,7,8, and 9 we will examine the full lifecycle of an AI or data science project in a company. From product development to model construction, evaluating its performance, and deploying it, you will be able to acquire a holistic idea of the way this process works in practice.Sections 10, 11, and 12 are very important ones too. You will learn how to manage data science and AI teams, and how to improve communication between team members. Finally we will make some necessary remarks regarding ethics, privacy, and bias.This course is an amazing journey and it aims to prepare you for a very interesting career path!Why should you consider a career as a Product Manager?Salary. A Product Manager job usually leads to a very well-paid career (average salary reported on Glassdoor: $128,992)Promotions. Product Managers work closely with division heads and high - level executives, which makes them the leading candidates for senior roles within a corporationSecure Future. There is a high demand for Product Managers on the job marketGrowth. This isn't a boring job. Every day, you will face different challenges that will test your existing skillsJust go ahead and subscribe to this course! If you don't acquire these skills now, you will miss an opportunity to distinguish yourself from the others. Don't risk your future success! Let's start learning together now!
