- Data Science
- Artificial Intelligence (AI)
- Machine Learning
- Predictive Analytics
- Modeling
- Artificial Neural Network
- Project Management
- Privacy
- Design Thinking
- Ethics
AI Product Management 專項課程
Manage the Design & Development of ML Products. Understand how machine learning works and when and how it can be applied to solve problems. Learn to apply the data science process and best practices to lead machine learning projects, and how to develop human-centered AI products which ensure privacy and ethical standards.
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您將學到的內容有
Identify when and how machine learning can applied to solve problems
Apply human-centered design practices to design AI product experiences that protect privacy and meet ethical standards
Lead machine learning projects using the data science process and best practices from industry
Identify and mitigate privacy and ethical risks in AI projects
您將獲得的技能
關於此 專項課程
應用的學習項目
Learners will implement three projects throughout the course of this Specialization:
1) In Course 1, you will complete a hands-on project where you will create a machine learning model to solve a simple problem (no coding necessary) and assess your model's performance.
2) In Course 2, you will identify and frame a problem of interest, design a machine learning system which can help solve it, and begin the development of a project plan.
3) In Course 3, you will perform a basic user experience design exercise for your ML-based solution and analyze the relevant ethical and privacy considerations of the project.
No programming experience or prior knowledge of machine learning / AI required.
No programming experience or prior knowledge of machine learning / AI required.
專項課程的運作方式
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Coursera 專項課程是幫助您掌握一門技能的一系列課程。若要開始學習,請直接註冊專項課程,或預覽專項課程並選擇您要首先開始學習的課程。當您訂閱專項課程的部分課程時,您將自動訂閱整個專項課程。您可以只完成一門課程,您可以隨時暫停學習或結束訂閱。訪問您的學生面板,跟踪您的課程註冊情況和進度。
實踐項目
每個專項課程都包括實踐項目。您需要成功完成這個(些)項目才能完成專項課程並獲得證書。如果專項課程中包括單獨的實踐項目課程,則需要在開始之前完成其他所有課程。
獲得證書
在結束每門課程並完成實踐項目之後,您會獲得一個證書,您可以向您的潛在雇主展示該證書並在您的職業社交網絡中分享。

此專項課程包含 3 門課程
Machine Learning Foundations for Product Managers
In this first course of the AI Product Management Specialization offered by Duke University's Pratt School of Engineering, you will build a foundational understanding of what machine learning is, how it works and when and why it is applied. To successfully manage an AI team or product and work collaboratively with data scientists, software engineers, and customers you need to understand the basics of machine learning technology. This course provides a non-coding introduction to machine learning, with focus on the process of developing models, ML model evaluation and interpretation, and the intuition behind common ML and deep learning algorithms. The course will conclude with a hands-on project in which you will have a chance to train and optimize a machine learning model on a simple real-world problem.
Managing Machine Learning Projects
This second course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the practical aspects of managing machine learning projects. The course walks through the keys steps of a ML project from how to identify good opportunities for ML through data collection, model building, deployment, and monitoring and maintenance of production systems. Participants will learn about the data science process and how to apply the process to organize ML efforts, as well as the key considerations and decisions in designing ML systems.
Human Factors in AI
This third and final course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the critical human factors in developing AI-based products. The course begins with an introduction to human-centered design and the unique elements of user experience design for AI products. Participants will then learn about the role of data privacy in AI systems, the challenges of designing ethical AI, and approaches to identify sources of bias and mitigate fairness issues. The course concludes with a comparison of human intelligence and artificial intelligence, and a discussion of the ways that AI can be used to both automate as well as assist human decision-making.
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杜克大学
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
常見問題
退款政策是如何规定的?
我可以只注册一门课程吗?
有助学金吗?
我可以免费学习课程吗?
此课程是 100% 在线学习吗?是否需要现场参加课程?
完成专项课程后我会获得大学学分吗?
完成专项课程需要多长时间?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
What will I be able to do upon completing the Specialization?
還有其他問題嗎?請訪問 學生幫助中心。