EEC 174 A/B: Senior Design Projects in Applied Machine Learning
In EEC 174 A/B, students will be introduced to challenges involved in designing and implementing components that are critical to data-driven and artificial intelligence (AI)-based control systems, including but not limited to data preprocessing, sensor fusion, computer vision (semantic segmentation, objection detection), machine learning (ML) based classification, and learning-based control systems. This is a team project that includes a final presentation and report. Example design projects include but not limited to: (1) implement learning modules for smart transportation (e.g., lane line detection, path finding, smart traffic light controller with reinforcement learning), (2) design and implement ML-driven clinical decision support system for smart healthcare applications. The students will work in teams of three or more.
Focus of EEC 174ABY
- Introduction to applied machine learning (ML) and deep learning
- Design and evaluate tasks critical to AI-driven control systems, e.g., sensor fusion, feature extraction/engineering, computer vision (segmentation and object detection), learning-based decision control
- Design themes: (a) self-driving cars and (b) smart health applications
Course Organization
Quarter 1
- Lecture & tutorial on data science, machine learning, and computer vision techniques
- First 5-6 weeks: guided labs using real or simulated datasets
- Second half of quarter: project matching & targeted pre-project tasks
Quarter 2
- Design, development, and evaluation of proposed systems/solutions.
- Weekly project check-in, mid-quarter progress report, final presentation and project report.