Nextbigfuture interviewed Dr. Mat Leonard of the Udacity School of AI. Udacity and Google have created a free course to help software developers to learn code AI applications.
There will be 3 to 4 lessons released every few weeks. The 14 lessons can be completed over 2 months. The coursework will take about 5 to 10 hours per week.
You can see the Nanodegree programs and free courses in the Udacity School of AI here:
Udacity works with industry leaders like Google, IBM and Amazon to build job-relevant education in fields like Natural Language Processing and Deep Learning.
The goal of the Udacity courses are to get you building state-of-the-art AI applications as fast as possible, without requiring a background in math. If you can code, you can build AI with TensorFlow. You’ll get hands-on experience using TensorFlow to implement state-of-the-art image classifiers and other deep learning models. You’ll also learn how to deploy your models to various environments including browsers, phones, and the cloud.
In 2016, Udacity released the very first free course on TensorFlow in collaboration with Google. Since then, over 400,000 students have enrolled in the course and joined the AI revolution. We’re excited to release an all-new version of this free course featuring the just-announced alpha release of TensorFlow 2.0: Intro to TensorFlow for Deep Learning. This update makes AI even more accessible to everyone, and we’ve again worked directly with the deep learning experts at Google to ensure you’re learning the very latest skills to utilize TensorFlow.
Google has standardized around Keras as the main API. This course focuses on Python for development.
The course will use the Google CoLab. This is cloud based access to GPUs for AI programming. Jupyter notebooks will also be used in the free course.
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.
Students will learn about Convolutional Neural Networks (CNN), data augmentation, and transfer learning. These techniques to increase the accuracy of deep neural networks and you’ll get hands-on experience by optimizing and testing your neural networks on different image datasets. Later in the course, you’ll learn how to deploy your trained models on browsers, Android, iOS, and embedded devices like the Raspberry Pi, as well as how to perform object detection, and much more.
This free course is part of Udacity’s School of AI, a set of free courses and Nanodegree programs designed by and for software developers.
SOURCES- Udacity, Interview Dr Matt Leonard
Written By Brian Wang