Overview of Udacity Artificial Intelligence Engineer Nanodegree, Term 1

#artificialintelligence

After finishing Udacity Deep Learning Foundation I felt that I got a good introduction to Deep Learning, but to understand things, I must dig deeper. Besides I had a guaranteed admission to Self-Driving Car Engineer, Artificial Intelligence, or Robotics Nanodegree programs.


How to Land An Autonomous Vehicle Job: Coursework -- Self-Driving Cars

#artificialintelligence

Recently I outlined a short series of posts I'll be writing about how I landed a job in autonomous vehicles. My background is that I have a pretty solid foundation in software engineering, including an undergraduate degree in computer science. But most recently my programming has been on the web, not so much in the machine learning and embedded systems areas that dominate vehicle software. Artificial Intelligence for Robotics (Udacity): This is a terrific and super-fun introduction into self-driving cars by Sebastian Thrun. Thrun is both the founder of Udacity and also the founder of Google's self-driving car project and also a former professor at Stanford.


5 Free Courses for Getting Started in Artificial Intelligence

@machinelearnbot

Don't know where or how to start learning? But learning more about artificial intelligence, and the myriad overlapping and related fields and application domains does not require a PhD. Getting started can be intimidating, but don't be discouraged; check out this motivating and inspirational post, the author of which went from little understanding of machine learning to actively and effectively utilizing techniques in their job within a year. With more and more institutes of higher learning today making the decision to allow course materials to be openly accessible to non-students via the magic of the web, all of a sudden a pseudo-university course experience can be had by almost anyone, anywhere. Have a look at the following free course materials, all of which are appropriate for an introductory level of AI understanding, some of which also cover niche application concepts and material.


5 Free Courses for Getting Started in Artificial Intelligence

#artificialintelligence

Don't know where or how to start learning? But learning more about artificial intelligence, and the myriad overlapping and related fields and application domains does not require a PhD. Getting started can be intimidating, but don't be discouraged; check out this motivating and inspirational post, the author of which went from little understanding of machine learning to actively and effectively utilizing techniques in their job within a year. With more and more institutes of higher learning today making the decision to allow course materials to be openly accessible to non-students via the magic of the web, all of a sudden a pseudo-university course experience can be had by almost anyone, anywhere. Have a look at the following free course materials, all of which are appropriate for an introductory level of AI understanding, some of which also cover niche application concepts and material.


5 Free Resources for Getting Started with Self-driving Vehicles

@machinelearnbot

Recent years have witnessed amazing progress in AI related fields such as computer vision, machine learning and autonomous vehicles. As with any rapidly growing field, however, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several topic specific survey papers have been written, to date no general survey on problems, datasets and methods in computer vision for autonomous vehicles exists. This paper attempts to narrow this gap by providing a state-of-the-art survey on this topic. Our survey includes both the historically most relevant literature as well as the current state-of-the-art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding and end-to-end learning. A lengthy, thorough overview, and probably the best starting place for anyone looking to get up to speed in the field quickly, and in one spot.