Intermediate Applied Artificial Intelligence in Mechanical Engineering

Course Description

This course offers an applied understanding of artificial intelligence (AI) and machine learning (ML). It covers topics such as machine learning models, Python essentials, and cloud-based platforms, and specialized subjects such as object detection, generative models, AI security, and natural language processing (NLP). Through a blend of theoretical instruction and hands-on exercises, students will master the algorithms, methodologies, and tools required to solve complex engineering challenges using AI. Students will develop ML models using TensorFlow and limited PyTorch, object detection techniques such as SSD (Single Shot Detector) and YOLO (You Only Look Once), generative models such as generative adversarial networks (GANs), and various NLP implementations. They will also learn how to secure AI systems against adversarial attacks and complete exercises on application programming interfaces (APIs), cloud computing, and web development frameworks such as Flask. Emphasis will be placed on real-world applications and state-of-the-art technologies to equip students with the skills required to implement AI solutions effectively and securely in various engineering contexts. Prerequisite(s): ***Mechanical Engineering students only: Must complete core course first (EN.535.641 Mathematical Methods for Engineers).

Code

EN.535.743

Credits

3

Subject

Mechanical Engineering

Programs That Include This Course

• Master's Mechanical Engineering, Master of Science