At Udacity, our priority is student success. While we continue to impact the lives of our students and the society at large, it is even more rewarding to witness the unique ways in which our students are making a difference in the world.
Such is the story of Ire Aderinokun, a Udacity Nanodegree graduate from Nigeria who has funded Udacity Nanodegree certificates for 17 other Nigerian women in the last two years. She personally started this scholarship program and is doing it only because she wants to create more success stories.
Today, we are excited to announce our newest offering to expand students’ machine learning deep learning skills: the DeepRacer Scholarship Challenge from Amazon Web Services (AWS).
This new scholarship program will enable students to acquire skills in machine learning and test their skills in the world’s first autonomous racing league – the AWS DeepRacer League. Top performing students in the DeepRacer League will also have the opportunity to earn their way to a full scholarship to the Machine Learning Nanodegree program with Udacity.
Today, Udacity is excited to announce the newest addition to our School of Programming: the Java Developer Nanodegree program. For over twenty years, Java has been one of the most popular programming languages in the world and remains one of the most popular programming languages today. A mainstay across industries, a majority of Fortune 500 companies rely on Java for their back-end development, and Java Developers had some of the fastest growing salaries of any job in the US in 2018!
Robots use a surprisingly simple but powerful algorithm to find out where they are on a map, a problem called localization by engineers. The algorithm known as particle filtering looks amazingly cool. In this first article, we attempt to explain the intuition behind particle filters. In part 2 we will elucidate the mathematics needed to build your own particle filters.
Every robot that can move around, whether it is a vacuum cleaning robot like a Roomba or a self-driving car like Carla, has a lifelong problem to contend with. The problem is to find out its whereabouts on a map that every robot carries with itself. But why is finding the whereabouts so challenging? A robot can just ‘look’ at its surroundings and recall which area on the map looks like the current surroundings, not very different from how we humans find where we are in a city or inside the office when woken up from a post-lunch slumber.
The challenge is the utmost precision with which robots have to localize themselves, very unlike humans. If a Roomba thinks it is in front of a door, while it actually is slightly behind a wall, a few centimeters away from where it thinks it is, it may never be able to maneuver its way out from one room to another. A self-driving car, operating under a similar misconception, may scrape another car, veer off the road or climb a curb. The reason this does not happen is because robots are able to beat humans at one of their own games.
Humans try to address the imprecision in their beliefs by filling in missing clues using logic and reasoning but they do end up tripping sometimes. However humans move around rather slowly and have enough time to recover from a bad assumption. So, while we may miss a step on a staircase and stumble, in most cases, we do not tumble down the staircase into the abyss.
For the sake of everyone’s safety robots pack much more precision into their beliefs so that they do not have to trip and recover. How do robots synchronize their beliefs with reality so precisely? Let us find out, starting with something called priors.
Here at Udacity, our students always come first and we’re constantly working to innovate and add value to our programs. We recently redesigned our Nanodegrees and launched new features that’ll better support our students on their career journey.
This week we have the privilege of hearing from Nunny Reyes — a climate change scientist turned front end developer thanks to Udacity’s Nanodegree program. Interested in a career change, Nunny turned to Udacity to get fundamental tech knowledge and real-world experience. Join us to hear more about the impact Udacity has had on her life and career.
With around 67% mobile penetration in the world and 5.1 billion mobile users globally, mobile technologies are growing at an unprecedented rate. This has resulted in huge demand for Android and iOS App developers.
Shivam dropped out of college where he was pursuing his Bachelors in Computer Science Engineering and strived hard to get hands-on with the concepts of coding which ultimately lead him to the Udacity Android Developer Nanodegree program. “Learning is a continuous process so keep learning and upgrading yourself with new technologies,” says Shivam Srivastava, Udacity Android Developer Nanodegree program graduate.
To prepare the next generation of product managers to compete in the AI-driven workforce of tomorrow, lifelong learning pioneer Udacity is announcing a new learning partnership with San Francisco-based machine learning and artificial intelligence company Figure Eight, an Appen company. Today, the two companies are announcing their collaboration on the AI Product Manager Nanodegree program, a course designed to teach students how to build AI-powered products and how to bring value to their business using AI.
“When product managers adopt and embrace AI to develop products with AI at their core, they can create an impressive impact on their bottom line and on the real world as a whole,” said Alyssa Simpson Rochwerger, Vice President of Product, Figure Eight. “We built this course with Udacity to empower professionals to help build amazing products using AI, but aren’t coming to the table with a deep technical background.”