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future Advanced 21 lessons

Autonomous Vehicles

Build the self-driving stack. Master Perception, Localization (SLAM), Path Planning, and Control logic using C++ and ROS.

Self-driving cars are the peak of robotics. This course breaks down the autonomous stack. You will learn Perception (using Cameras/Lidar to see), Localization (knowing where the car is), and Path Planning (deciding where to go). We implement PID controllers to steer the vehicle smoothly. Using the CARLA simulator, you will write code that drives a virtual vehicle through traffic, adhering to traffic laws and avoiding obstacles.

✅ 100% Free & Lifetime Access
⏱️ 5-Minute Lessons (Bite-sized learning)
🚀 21-Lesson Path (Independent modules)
📱 Mobile Friendly (Learn anywhere)
Robotics
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Complete Course Syllabus

  • 1
    The AV Stack
    Sensors, Perception, Planning, and Control layers.
  • 2
    Computer Vision
    Detecting lanes and traffic lights with OpenCV.
  • 3
    Sensor Fusion
    Combining Lidar and Radar data for accuracy.
  • 4
    Localization
    Particle Filters and knowing where you are on the map.
  • 5
    Path Planning
    Generating smooth trajectories through traffic.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary
$130k - $190k

Career Paths

Autonomous Driving Eng $140k-$200k
Perception Engineer $135k-$190k
Robotics Scientist $130k-$180k

What You Will Learn

Implement Computer Vision for lane and object detection
Perform Localization using Kalman Filters and SLAM
Plan paths using A* and behavioral logic
Control vehicle steering/throttle using PID controllers
Test algorithms in the CARLA high-fidelity simulator

Skills You Will Gain

Computer Vision Sensor Fusion Path Planning Control Theory C++ / Python

Who Is This For

Robotics Engineers
CV Specialists
Auto Engineers

Prerequisites

C++
Linear Algebra

Autonomous Vehicles FAQs

Real car?

No, we use the CARLA open-source simulator.

Hard?

Yes, combines advanced math, physics, and code.

Hardware?

Needs a GPU to run the 3D simulator efficiently.

C++ or Python?

Prototyping in Python, performance code in C++.

Need more info?
All Reork courses are 100% free, self-paced, and fully accessible on mobile devices. No prior experience is required. Read our full Platform FAQ.

Tech Stack & Tools

CARLA Simulator
ROS
OpenCV
PCL (Point Cloud)

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