The goal of Artificial intelligence is quite simple: To help humans work more efficiently by taking on some of their tasks. It’s achieved by AI programs utilizing some very human-like characteristics themselves. To learn artificial intelligence isn’t that easy and it will always remain a difficult one. However, the access to Artificial Intelligence has become easier than before.The availability of online classes along with the actual classroom has made its access easier. Such type of classes covers not only Artificial Intelligence but also topics such as machine learning and deep learning.
Learning with Google AI
It has been planned and started by Google to extend the learning with Artificial Intelligence Online Course to the common people. It is adding the material gradually but this already includes a Machine Learning with TensorFlow (Google’s machine learning library) crash course.
The range of the course is from the ground to basic introduction to machine learning, to getting started with TensorFlow, to designing and training neural nets.
It has been designed in order to enable a person having no background of machine learningto jump straight in the start, those havinglittle exposure could select or opt for those modules which attracts them most, whereas machine learning experts could utilizethis as an introduction to TensorFlow.
Google Machine Learning
The Google-Machine Learning is a somewhat lengthy and detailed course from Google which is run through Udacity. However, it doesn’t point at whole novices and it is taken for granted that there is previous experience of machine learning, to the point where you are at least familiar with supervised learning methods.
The entire course is focussedon deep learning, and the models of auto-teaching systems that can learn from large, complex datasets.
This course has been designed looking forward to put machine learning, neural network technology to work as data analysts, data scientists or machine learning engineers as well as enterprising individuals wishing to make use of the surplus of open source libraries and materials available.
Introduction to Machine Learning
The data is available now a days in abundance from varied sources and it has been observed that there is an increase in demand in thedifferent data driven fields such as analytics and machine learning. In this course of Machine Learning the objective is to introduce some of the basic concepts of machine learning from a mathematically well motivated perspective. The course will cover the different learning models and some of the more popular algorithms and architectures used in each of these models.
This is an elective course intended for senior UG / PG Artificial Intelligence Engineering students.
BE/ME/MS/PhD PREREQUISITE: We will assume that the students know programming for some of the assignments. If the students have doneintroductory courses on probability theory andlinear algebra it would be helpful. We will review some of the basictopics in the first two weeks as well.