Udacity and Deeplearning.ai launch TensorFlow 2.0 online training courses
The latest version of TensorFlow prioritizes use of Eager execution and comes with a number of upgrades, including the elimination of several APIs in exchange for reliance on APIs from the Keras deep learning library, starting with Keras Sequential API.
Intro to TensorFlow for Deep Learning will be a free course for software developers on Udacity, while enrollment in part one of the deeplearning.ai TensorFlow Specialization opened today.
More than 400,000 students have enrolled in a Udacity TensorFlow training program since the course was first introduced in 2016.
Dr. Laurence Moroney will teach the deeplearning.ai course. Moroney worked with Coursera cofounder and deeplearning.ai cofounder Andrew Ng to develop the coursework and syllabus designed to help developers train, understand, and improve their neural nets.
Remaining courses in the TensorFlow: From Basics to Mastery Specialization series of courses will be made available in the coming months, a company spokesperson told VentureBeat in an email.
A Fast.ai training course is also being introduced today for TensorFlow Lite for mobile developers.
Combined, Fast.ai, Udacity, and deeplearning.ai represent some of the most popular open online courses for people with some understanding of computer science or programming to learn how to train and deploy machine learning models.
The launch comes a day after Udacity introduced a data engineering nanodegree program, and a week after the launch of AI for Everyone, a Coursera-deeplearning.ai course for people without experience in machine learning.
More to come
