This course explores advanced AI & ML techniques, ending with a comprehensive capstone project. You will learn about cutting-edge ML methods, ethical considerations in GenAI, and strategies for building scalable AI systems. The capstone project allows students to apply all their learned skills to solve a real-world problem.


Advanced AI and Machine Learning Techniques and Capstone
本课程是 Microsoft AI & ML Engineering 专业证书 的一部分

位教师: Microsoft
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- 通过 Microsoft 获得可共享的职业证书

该课程共有4个模块
This advanced module delves into cutting-edge methodologies that enhance the performance, efficiency, and privacy of ML systems. By the end of this module, you'll have hands-on experience with these advanced techniques, equipping you with the skills to tackle complex ML challenges and contribute to cutting-edge research and development.
涵盖的内容
12个视频17篇阅读材料11个作业1个插件
This module provides an in-depth exploration of the ethical and human-centric considerations essential to the development and deployment of AI and ML systems. By the end of this module, you'll be equipped to critically assess and address the ethical, human, and organizational challenges posed by AI technologies, ensuring that your work aligns with both technical excellence and societal values.
涵盖的内容
11个视频11篇阅读材料5个作业1个插件
This module focuses on designing and implementing distributed computing solutions to handle large-scale ML challenges efficiently. This module equips you with the knowledge and skills needed to build and optimize ML systems for high-throughput and scalable environments. By the end of this module, you'll be adept at designing, implementing, and optimizing distributed ML systems that can efficiently tackle large-scale problems, while balancing performance and cost considerations to meet organizational and project needs.
涵盖的内容
7个视频12篇阅读材料8个作业1个插件
This module provides a comprehensive exploration of the professional and strategic aspects of working as an AI/ML engineer within a corporate environment. It will guide you through the key responsibilities, ethical considerations, and strategic decision-making processes relevant to the field. By the end of this module, you will be well equipped to navigate your professional responsibilities, implement ethical AI practices, manage cost-performance trade-offs, and communicate effectively with stakeholders, positioning yourself as a valuable contributor in the corporate AI landscape.
涵盖的内容
7个视频11篇阅读材料7个作业1个插件
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常见问题
To be successful in this course, you should have intermediate programming knowledge of Python, plus experience with AI & ML infrastructure, core AI & ML algorithms and techniques, the design and implementation of intelligent troubleshooting agents, and Microsoft Azure’s AI & ML services. Familiarity with statistics is also recommended.
You will need a license to Microsoft Azure (or a free trial version) and appropriate hardware. Note: the free trial version of Azure is time limited and may expire before completion of the program.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。