Udacity, an online learning educational courses provider, in conjunction with Deeplearning.ai, a company that explores the frontier of Artificial Intelligence, has announced to launch new training courses that will assist people to use TensorFlow 2.0, which was released very recently. The newest version of TensorFlow prioritizes the use of Eager execution and came with a number of improvements, including the removal of a range of APIs in return the dependency on APIs from the Keras Deep Learning library, starting with Keras Sequential API. TensorFlow’s eager execution is an imperative programming environment that analyzes operations instantly.
For grasping the opportunity of Udacity TensorFlow online training courses, over 400,000 students have enrolled since the course was first launched in the year 2016. Intro to TensorFlow for Deep Learning will be a free course for software developers on Udacity, while enrollment to participate in one of the Deeplearning.ai TensorFlow Specialization opened by 6th February. A Fast.ai training course is also being introduced on the same day for TensorFlow Lite for mobile developers. The collaboration between Fast.ai, Udacity, and Deeplearning.ai represent all the rage open online courses for people with some understanding of computer science or programming to learn about how to coach and deploy Machine Learning models. For the training courses, AI developer Dr. Laurence Moroney will teach the Deeplearning.ai course. Moroney has worked with Coursera co-founder and Deeplearning.ai cofounder Andrew Ng to make the coursework and syllabus that will help developers to train, understand, and advance their neural nets.
According to the reports, remaining courses in the “TensorFlow: From Basics to Mastery Specialization” series will be rolled out in the coming months. The announcement of TensorFlow 2.0 online training courses came after a day when Udacity launched a data engineering nano degree program, and later a week of the launch of “AI for Everyone,” a Coursera-Deeplearning.ai course for people lack experience in Machine Learning.