"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
Dieser Kurs ist Teil von Spezialisierung AI for Mechanical Engineers
Dozent: Wei Lu
Bei 
enthalten
Empfohlene Erfahrung
Was Sie lernen werden
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
Wichtige Details
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Dezember 2024
3 Aufgaben
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In diesem Kurs gibt es 3 Module
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.
Das ist alles enthalten
2 Videos5 Lektüren1 Aufgabe1 Unbewertetes Labor
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.
Das ist alles enthalten
2 Videos2 Lektüren1 Aufgabe1 Unbewertetes Labor
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.
Das ist alles enthalten
2 Videos3 Lektüren1 Aufgabe
Dozent
Empfohlen, wenn Sie sich für Mechanical Engineering interessieren
Johns Hopkins University
Simplilearn
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