In this repository you can find my own solutions to the Flying Car Nanodegree Program projects.
- Link: Intro to Self Driving Cars Nanodegree
- Description: Work on self-driving car problems using Python, C++, matrices and calculus in code, and computer vision/machine learning.
This section enumerates the courses taken in this nanodegree and the projects completed
Bayesian thinking involves the mathematical framework that underlies a self-driving car's understanding of itself and the world around it. This course presents the localization methodology used by the self-driving car to accurately estimate of its location in the world.
- Project: 2D Histogram Filtering
This course introduces the usage of C++ in self-driving cars. The project involves the translation of a given program written in Python into C++
- Project: Implement a matrix class
This course focuses on how to write good code that runs correctly. Primary focus is made on the low level language features of C++ which can make C++ fast.
- Project: Translate Python to C++
Navigating Complex Data Structures involves the algorithm implementation based on Algorithmic thinking that show up most frequently in self-driving cars.
- Project: Planning and Optimal Path
You will learn the basics of calculus, the mathematics of continuity. Also, you will learn to use some of Python's most popular visualization libraries.
- Project: Reconstructing Trajectories