"AI for Energy and Biomedical Applications” explores the groundbreaking applications of AI technologies revolutionizing energy systems and advancing healthcare solutions. In the energy sector, AI is reshaping how we generate, distribute, and manage energy resources. From optimizing renewable energy production to enhancing energy efficiency and grid management, AI offers unprecedented opportunities for sustainability and resilience. Through this course, you will explore AI-driven techniques such as predictive maintenance, demand forecasting, and energy storage optimization, empowering you to drive innovation and address pressing energy challenges. In the realm of biomedical applications, AI is driving breakthroughs in disease diagnosis, drug discovery, and personalized medicine. You’ll delve into AI-driven approaches to medical image analysis, genomic data interpretation, and predictive modeling of disease progression. You’ll also gain insights into how AI is revolutionizing healthcare delivery, enabling early detection of diseases, and facilitating precision medicine tailored to individual patients.
AI for Energy and Biomedical Applications
本课程是 AI for Mechanical Engineers 专项课程 的一部分
位教师：Wei Lu
2,006 人已注册
包含在 
中
您将学到什么
Gain proficiency with AI techniques for energy optimization
Develop an understanding of AI applications in biomedical sciences
Experiment with AI approaches to address energy and biomedical problems
您将获得的技能
- Medical Science and Research
- Machine Learning
- Precision Medicine
- Bioinformatics
- Deep Learning
- Predictive Modeling
- Molecular Biology
- Image Analysis
- Electric Power Systems
- Applied Machine Learning
- Medical Imaging
- Artificial Intelligence
- Artificial Neural Networks
- Generative AI
- Sustainable Technologies
- Energy and Utilities
- Anomaly Detection
- Pharmaceuticals
要了解的详细信息
添加到您的领英档案
3 项作业
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有3个模块
In module 1 we will review challenges that we may face energy optimization. Then, we will explain different AI-driven energy optimization techniques including demand forecasting, load management, and renewable energy integration. Finally, we will examine AI-driven optimization strategies for energy storage systems.
涵盖的内容
2个视频5篇阅读材料1个作业1个非评分实验室
In module 2, we explain predictive maintenance principles and continue to review AI driven predictive maintenance techniques including machine learning, deep learning, and anomaly detection algorithms. We explain how predictive maintenance models can be trained and optimized. Finally, we discuss strategies for integrating AI-driven predictive maintenance models into existing energy infrastructure systems.
涵盖的内容
2个视频2篇阅读材料1个作业1个非评分实验室
In module 3, we review how AI techniques are used to analyze medical images and to interpret genomic data. We will discuss how AI has impacted drug discovery and other biomedical applications.
涵盖的内容
2个视频4篇阅读材料1个作业
获得职业证书
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位教师
从 Mechanical Engineering 浏览更多内容
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