CV for Autonomous Vehicles
This track covers the complete perception stack for autonomous systems. Learn to build, train, and deploy the computer vision models that power self-driving vehicles and intelligent robots.
12Lessons
~6hContent
5Chapters
∞Access
What You'll Learn
3D Object Detection
Multi-Object Tracking
Sensor Fusion
BEV Perception
ROS2
Curriculum
Chapter 1
Perception Fundamentals
2 lessons- 1.1The Autonomous Perception Stack20 min
- 1.2Sensor Types & Data Formats25 min
Chapter 2
2D & 3D Detection
3 lessons- 2.12D Object Detection for Driving25 min
- 2.2LiDAR-based 3D Detection30 min
- 2.3Camera-only 3D Detection (BEV)30 min
Chapter 3
Tracking & Prediction
2 lessons- 3.1Multi-Object Tracking25 min
- 3.2Trajectory Prediction25 min
Chapter 4
Sensor Fusion
2 lessons- 4.1Camera-LiDAR Fusion30 min
- 4.2Temporal Fusion25 min
Chapter 5
Deployment
3 lessons- 5.1TensorRT Optimization25 min
- 5.2ROS2 Integration30 min
- 5.3Safety Validation20 min
What's Included
🤖
AI Learning Companion
Ask questions and get instant explanations powered by Google Gemini.
📜
Completion Certificate
Shareable, verifiable certificate to showcase on LinkedIn.
💻
Practical Exercises
Build real projects with industry datasets and production-ready code.
♾️
Lifetime Access
Access your course forever. All future updates included.
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Lifetime access to all 12 lessons, AI companion, and completion certificate.