Artificial Intelligence

What's the course about

In the present world, technology is refining very agile and every day we are getting in touch with various new technologies, machines, devices, etc. Human is the creator of such great devices which have a compact size, high speed and can make our life very simple. Now, Artificial Intelligence is the booming technology in computer science which is ready to build a new revolution in the world by building machines with brains.

Just a daydream in the domains of science fiction, artificial intelligence (AI) is now mainstream technology in our usual lives with applications in image and voice recognition, language translations, chatbots, and predictive data analysis.

A vital part of artificial intelligence deals with outlining or deliberation for a system which can perform mechanical motions. This sort of processing requires input provided by a computer vision system, acting as a vision sensor and providing high-level information about the moving system. The computer vision system is composed of various perspectives such as image recognition, object detection, image generation and many more.

For creating scalable AI-powered algorithms, you need to learn the way of using tools to build them. TensorFlow can be used for Object Detection on images or videos. TensorFlow provides an API that helps you do it. Robot Navigation: Deep Learning using TensorFlow can be used to train robots to perform human tasks.

Course objective:

All complex real-world problems like self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection are solved with Artificial Intelligence (AI). The main objective of this course is to give a comprehensive knowledge of the basic techniques for creating intelligent computer systems and a perception of how AI is applied to problems by introducing AI’s key problems, and the state-of-the-art models and algorithms used to undertake these problems. The course is outlined to provide a summary of AI concepts and workflows, machine learning and deep learning, OPEN-CV, TensorFlow and statistics essentials while providing a sufficiently strong foundation to encourage further research.