Self-Driving Car Nanodegree Projects Summary

Here is a summary of what topics and technology stack I had learned during Self-Driving Car Engineer Nanodegree Program:

1. Computer Vision and Deep Learning (Term 1)

   • topics (including project implementation):
     1. Finding Lane Lines on the Road
     2. Traffic Sign Classifier
     3. Behavioral Cloning
     4. Advanced Lane Finding
     5. Vehicle Detection and Tracking
   • technology stack:
     1. Python
     2. Jupyter Notebook
     3. OpenCV
     4. TensorFlow
     5. Keras

2. Sensor Fusion, Localization and Control (Term 2)

   • topics (including project implementation):
     1. Extended Kalman Filters
     2. Unscented Kalman Filters
     3. Particle Filter
     4. PID Controller
     5. Model Predictive Control
   • technology stack:
     1. C++
     2. Eigen Library

3. Path Planning, Concentrations, and Systems (Term 3)

   • topics (including project implementation):
     1. Path Planning
     2. Semantic Segmentation
     3. System Integration
   • technology stack:
     1. C++
     2. Eigen Library
     3. Python
     4. TensorFlow
     5. ROS