AI for Energy and Biomedical Applications

Instructor: Wei Lu

Intermediate Level • 6 hours to complete 3 weeks at 2 hours a week • Flexible Schedule

What You'll Learn

  • 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

Skills You'll Gain

Pharmacology
Applied Machine Learning
Bioinformatics
Artificial Intelligence and Machine Learning (AI/ML)
Predictive Analytics
Health Informatics
Artificial Intelligence
Precision Medicine
Deep Learning
Electric Power Systems
Anomaly Detection
Medical Imaging
Image Analysis
Predictive Modeling
Energy and Utilities
Machine Learning Algorithms

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

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.

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.

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.