Udacity – Intro to Self-Driving Cars nd113 v1.0.0 2018-12

Intro to Self-Driving Cars is an introductory self-driving car training course published by Udacity Specialized Academy. This 4-month training course is one of the most important and complete courses available in the field of self-driving cars on the Internet, taught by a group of experienced experts. This training course contains a series of scattered but very practical topics such as Python and C++ programming languages, matrices and applied calculations, computer vision and machine learning. Is. All these topics are used in solving problems and challenges in the field of self-driving cars, and by putting together the potentials of each, we will be able to develop 100% self-driving and intelligent cars.

This training course is not recommended for beginner students and the student is expected to have some background knowledge in the fields of introductory algebra and reading and editing Python and C++ codes.

What you will learn in Intro to Self-Driving Cars

• Bayesian inference
• Principles and basics of self-driving car design
• Ways of understanding and observing the environment by self-driving cars
• Object-oriented programming and its importance in the development of self-driving cars
• Linear algebra and matrices
• The basics of Python and C++ programming languages
• Complex data structures
• Algorithm writing and algorithmic thinking
• Advanced and functional accounts
• Using different libraries and frameworks based on Python for visualization of data and mathematical problems
• machine learning
• computer vision
• And …

Course specifications

Publisher: Udacity
Instructors: Sebastian Thrun, Andy Brown, Cezanne Camacho, Andrew Paster, Anthony Navarro, Elecia White and Tarin Ziyaee
Language: English
Level: Intermediate
Number of Lessons: 41
Duration: Approx. 4 Months

Course topics

Part 01 : Orientation

Module 01: Welcome to Intro to Self-Driving Cars!

Module 02: Readiness

Part 02 : Bayesian Thinking

Module 01: Bayesian Thinking

Part 03 : Working with Matrices

Module 01: Working with Matrices

Part 04 : C++ Basics

Module 01: C++ Basics

Part 05 : Performance Programming in C++

Module 01: Performance Programming in C++

Part 06 : Navigating Data Structures

Module 01: Navigating Data Structures

Part 07 : Vehicle Motion and Control

Module 01: Vehicle Motion and Control

Part 08 : Computer Vision and Machine Learning

Module 01: Computer Vision and Machine Learning

Part 09 : Graduation!

Module 01: Congratulations!

Module 02: Guaranteed Admission into your next Nanodegree

Intro to Self-Driving Cars Prerequisites

Students should have some experience with programming—writing short scripts in a programming language—and be comfortable with algebra. You should also feel comfortable reading and modifying code that you are given, with the understanding that solving problems in code may still be challenging. If you believe you need more preparation, here are some additional resources you can use:

Free Courses

• Intro to Computer Science
• Programming Foundations with Python
• Intro to Statistics, Descriptive Statistics and Inferential Statistics
• Linear Algebra Refresher
• Intro to Data Science and Data Analysis
• Statistics and Probability (Khan Academy)

Paid Programs

• Intro to Programming Nanodegree Program
• Data Analyst Nanodegree Program

What software and versions will I need in this program?

For this Nanodegree program, you will need to have the minimum equipment requirements outlined here: https://www.udacity.com/tech-requirements.

Which version of TensorFlow, Keras, ROS, and C++ are taught in this program?

• TensorFlow Version 1.3
• Keras version 2
• ROS Kinetic
• Python Version 3
• C++ Version 11

Pictures

Intro to Self-Driving Cars introduction video

Installation guide

In order to view the lessons of the course in an organized and regular manner, run the index.html file and run the videos through this file.

English subtitle

Quality: 720p

download link

Download Part 1 – 1 GB

Download Part 2 – 1 GB

Download Part 3 – 1 GB

Download Part 4 – 398 MB

Size

3.4 GB