Course Overview
🎯 Course Description
Welcome to ELEC 395, an intensive hands-on laboratory course where you'll build, program, and deploy artificial intelligence systems on real hardware. This course bridges the gap between AI theory and practical engineering implementation using NVIDIA Jetson Orin Nano Developer Kits and autonomous robot platforms.
Throughout this course, you'll progress from hardware fundamentals and Python programming to advanced topics including deep neural networks, computer vision, and autonomous navigation. Every week combines theoretical foundations with practical implementation, culminating in a comprehensive AI robotics project.
🌟 What Makes This Course Unique
- Real Hardware: Work with professional-grade NVIDIA Jetson platforms used in industry
- Hands-On First: Build working AI systems every week, not just theory
- Progressive Learning: Start with basics, advance to cutting-edge autonomous systems
- Industry Tools: Use PyTorch, OpenCV, and frameworks powering real-world AI applications
- Complete Project Cycle: Experience the full engineering lifecycle from hardware setup to deployment
Learning Outcomes
Upon successful completion of this course, students will be able to:
ML, AI & IoT Fundamentals
Understand the basics of machine learning, artificial intelligence and IoT [PLO-6]
Data Analysis
Analyze datasets using machine learning methods for regression and classification [PLO-6]
Data Acquisition & Sensors
Explore data acquisition and sensor interface platforms [PLO-6]
AI for IoT Applications
Develop AI skills for machine learning in IoT based applications such as home-automation, smart health, robotics, autonomous driving etc. [PLO-6]
Teamwork & Communication
Demonstrate ability to work with a group and communicate findings effectively [PLO-5]
Course Schedule
Grading & Assessment
| Component | Weight | Description |
|---|---|---|
| Lab Reports | 45% | Weekly laboratory reports (13 reports, best 10 count) |
| Term Project | 25% | Comprehensive AI robotics project with presentation |
| Final Examination | 30% | Written and practical comprehensive assessment |
| TOTAL | 100% |
📋 Important Grading Policies
- Lab Reports: Due one week after lab completion; late submissions accepted within 48 hours with 20% penalty
- Best 10 of 13: Your best 10 lab reports count toward your grade, allowing for flexibility
- Attendance: Mandatory for all lab sessions; missing 3+ labs may result in course failure
- Term Project: Proposals due Week 8; final presentations Week 14
- Academic Integrity: All work must be your own; violations result in zero credit and disciplinary action
Course Resources
💬 Discord Community
Join our course Discord server for real-time discussions, troubleshooting help, and collaboration with classmates.
Join Discord📁 Microsoft Teams
Access lecture recordings, lab materials, announcements, and submit your assignments through Teams.
Open Teams⏰ Lab Hours
Open lab sessions every Tuesday and Thursday 2-4 PM for hands-on assistance with hardware and coding.
Schedule🐍 Python Tutorial
Comprehensive Python programming guide covering basics through advanced topics essential for AI/ML development.
Start Tutorial🤖 AI Fundamentals
Essential concepts in artificial intelligence and machine learning, from basic principles to practical applications.
Learn MoreTips for Success
📌 Recommended Lab Strategy
- Before Lab: Review the lab manual and watch assembly videos to understand objectives
- During Lab: Follow safety protocols, document your work with photos, ask questions immediately
- Hardware Setup: Double-check all connections before powering on any device
- Coding: Test code incrementally - don't wait until the end to run everything
- Documentation: Keep a lab notebook with observations, errors, and solutions
- Collaboration: Work with partners but ensure you understand every component
- Project Work: Start early on term projects - hardware debugging takes time
- Resources: Use Discord for quick help and share useful discoveries with classmates
⚡ Common Pitfalls to Avoid
- Not backing up your code regularly - use Git!
- Skipping pre-lab preparation - you'll waste valuable lab time
- Ignoring error messages - they're trying to help you
- Not testing hardware connections before running code
- Working alone when stuck - use the support channels
Contact Information
Dr. Mohammad Al Bataineh
Email: [email protected]
Office: F1-1175
Phone: +971 3 713 5146
Website: Faculty Page
Lab Support Hours
Open Lab: Tuesday & Thursday
Time: 2:00 PM - 4:00 PM
Location: AI Lab - E6 Building
Also available via Discord and email appointment
Teaching Assistants
Hardware Support: Available during all lab sessions
Programming Help: Discord support channel
Project Guidance: By appointment
Additional Support
♿ Special Needs Services
Students requiring lab accommodations or assistive technologies should contact the Special Needs Services Center.
Phone: +971 3 7134264
Email: [email protected]
🛠️ Technical Support
IT support for software installation, network access, and computing resources for AI/ML development.
IT Helpdesk: +971 3 713 6111
Email: [email protected]
📖 Library Resources
Access to IEEE Xplore, ACM Digital Library, and AI/ML textbooks through the university library.
Library Portal