The table below shows an abbreviated syllabus of the udacity nanodegree "self-driving car engineer", which I completed successfully. Please follow the links to find my solutions for the assigned projects of the second half of the program. For a more detailed syllabus, go to https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd013.
| Topic | Lessons | Project (with link to my repo) |
|---|---|---|
| Introduction | Welcome, Workspaces | |
| Computer Vision | Computer Vision Fundamentals | Finding Lane Lines on a road |
| Advanced Computer Vision | Advanced Lane Finding | |
| Deep Learning | Neural Networks, TensorFlow, Deep Neural Networks, Convolutional Neural Networks | Traffic Sign Classifier |
| Keras, Transfer Learning | Behavioral Cloning | |
| Sensor Fusion | Sensors, Kalman Filters, C++ Checkpoint, Extended Kalman Filters | Extended Kalman Filters |
| Localization | Introduction, Markov Localization, Motion Models, Particle Filters | Kidnapped Vehicle |
| Path Planning | Search, Prediction, Behavior Planning, Trajectory Generation | Highway Driving |
| Control | PID Control | PID Controller |
| System Integration | Autonomous Vehicle Architecture, Introduction to ROS, Packages and Catkin Workspaces, Writing ROS Nodes | Capstone project |