The course is an introduction to the basics of deep learning methods. You start with object detection and tracking, in which you track faces, objects and eyes. You then learn to build a neural network and an Optical Character Recognition (OCR) and also how to build learning agents that can learn from interacting with the environment. You use Deep Learning with Convolutional Neural Networks, and use TensorFlow to build neural networks. Subsequently you will build an image classifier using Convolutional Neural Networks.
This video-based course is built for those with a basic understanding of Artificial Intelligence, introducing them to advanced Artificial Intelligence projects as they go ahead. The first module introduces Object Detection and Tracking, and then Artificial Neural Networks Reinforcement Learning and Deep Learning with Convolutional Neural Networks.
This course comes along with a community - Artificial Intelligence with Python - Deep Neural Networks. Once you purchase the course, you become a part of this community. You can enhance your learning by participating in the discussion threads, raise queries and get solutions through the community in quick time. You can also share your own ideas, access best practices shared by peers, get ideas about the next learning topics to complete your study. You may also participate in the ongoing discussion forums to raise and clear your doubts. You are also encouraged to go through all the topics of the course in detail and post your queries in the applicable comments section of the community. The moderator of the community will get back to you within a short time.
On completion of the course, you can build applications based on deep learning algorithms, detect and track objects using different algorithms and understand how reinforcement learning works.
Python programming knowledge is required.