Goal: To Advance Career | Salary: ₹50 lakh | Nanodegree | Proficiency in Programming, Algebra and Statistics Needed | Taught by Udacity Instructors | Duration: 4 Months
A program that will help you specialise in the upcoming driverless car technologies. You learn the essentials of programming a self-driving car, from machine learning to object-oriented programming to probabilistic robotics.
You should have experience with programming including reading, writing and modifying code, in addition to knowledge of Data Science and Data Analysis. Moreover, you should have some strong knowledge of linear algebra, statistics and probability.
Note: You should take up the Self-Driving Car Engineer Nanodegree program after this program so you can unlock the actual value of your specialisation.
What You’ll Learn
- Learn the framework that underlies a self-driving car’s understanding of itself and the world around it
- How to work with matrices. The program will focus on two vital tools for self-driving car engineers: object oriented programming and linear algebra
- C++ basics including writing a program in Python and translating it into C++. Optimise functioning but inefficient C++ code to avoid cycles or memory wastage
- Navigate complex data structures and visualise calculus and controls
- How to use machine learning to teach a computer to identify images programmatically
What You’ll Earn
- ₹50 lakh per year is the average starting salary for a Driverless Car Engineer in India (Source: businesstoday.in, businessinsider.in)
- $200,000+ per year is the average salary for a Driverless Car Engineer in the US (Source: businesstoday.in, businessinsider.in)
Details
This program will sharpen your Python skills and teach you how to apply C++, matrices and calculus in code. In addition, you will learn about computer vision and machine learning.
Here are the skills you will learn:
- Python: Python Syntax, Python Data Structures, Python Arrays
- C++: C++ Syntax, C++ Libraries, C++ Functions, C++ Code Optimization
- Probability and Statistics: Probability Distribution, Basic Probability, Bayes’ Theorem
- Trigonometry: Pythagorean Theorem
- Calculus: Integrals, Derivatives
- Algebra: Vectors, Matrix Operations
- Data Structures and Algorithms: Search Algorithms, Histogram Filters, Algorithmic Problem Solving
- Object-Oriented Programming: Classes, Object-Oriented Programming Basics
- Robotics: Object Localization, Object Motion Models
- Computer Vision: Image Pre-Processing, Computer Vision Fluency
- Digital Signal Processing: Image Transformations
Applied Learning Project
The program gives you intensive hands-on training on real-world problems related to driverless cars. Over the course of the program, you will, among other things:
- Write code to control a simulated vehicle including sending throttle and steering commands to the car to navigate around a test track
- Write the sense and move functions for a 2-dimensional histogram filter in Python
- Use graph data structures and search algorithms to write an algorithm which uses a map and traffic information to find the quickest route between two points
- Write a visualization tool that will let you visualize the continuous trajectories that come from various search and control algorithms
- Build an image classifier from scratch to reliably classify an image as ‘pedestrian’ or ‘car’
