World of Artificial Intelligence - B.tech Artificial intelligence

Artificial intelligence (AI) is wide-ranging area of engineering concerned with build modern technology capable of performing everyday jobs that characteristically require human intelligence. AI is an interdisciplinary science with manifold approaches, but advancements in machine learning and deep learning are creating a standard shift in practically every sector of the production. Students can make a very bright future in the field of artificial intelligence engineering. Artificial intelligence (AI) provides privilege to the machines to learn from experience, regulate to new inputs and perform man-like tasks. Most AI examples that you hear in your today life like computers playing chess, self-driving cars, Voice changing software, rely heavily on deep learning and natural language processing. Using these technologies large amount of data can be processed by the computer to perform unique task.

Why we need artificial intelligence

Artificial Intelligence in Medical world: We are living in a digital world where most of thing could be done via technology and Internet. Nowadays we get to see that from a remote location a doctor/nurse can monitor and diagnose the disease of a patient. Imagine the same way where the patient’s medical problem will test against predefined medications and code algorithms prescribed a solution to the doctor. This would be building a huge change in the entire medical world.

Artificial Intelligence in Modern Home: In last few years, we have seen a lot of modern devices coming up in the word which are working in line with our requirements. So mainly based on your required patterns, the electricity in the house and temperature of the air conditioner etc can definitely be watched and ultimately developed best possible consumption settings as well. All of these are happening because of use of machine learning and Artificial Intelligence.

Artificial Intelligence in Automobile world: If you are familiar with the current technology accomplishments then you wouldn’t have missed. The idea of diver less cars and pilotless airplane are in the news recently and big companies like “Google” and “Tesla” are already in this field. Can you ever imagine that you are being sitting in a driver less car take you from location to other location? Well, now this is not a dream in Today world, a lot of experiments runs have gone through were the concept cars going to hit the person. This is surely to be the new era of the automobile world.

Students as well as professional person can built a very good career in the field of artificial intelligence. In Delhi/NCR IIMT College of Engineering, Greater Noida offer B.Tech course in artificial intelligence. This college is affiliated to Dr. A.P.J. Abdul Kalam Technical University, Luck now. This is NBA accredited college and full fills all the requirements of best engineering colleges in UP as well as in India. A part from course in Artificial intelligence this college also offers managements courses like MBA, BBA, BCA, and B.Com. The other engineering courses are B.Tech in CSE/ECE/ME/CE/IT. In the legal and medicine field this college also offer course in LAW and Pharmacy.

MACHINE LEARNING A VERSATILE CAREER DOMAIN

       In machine learning, a neuron is a simple, yet integrated processing device that works with external input. The neuron receives the data according to its input, processes the data using metals, selections, and aperture function, and then sends the result forward as output. Once you have found a neuron that captures input data and generates value, you will need to train it by adjusting the weights and portability within the neuron until the result is correct.
     Machine Learning uses these neurons in various tasks such as guessing the outcome of an event, such as a stock price, or even a player's movement during a game. The neuron uses input data from any previous events to predict the outcome.

What can machine learning do?
   One of the problems of machine learning is learning about guarding. These are problems where there is training data available so the system can get feedback on its performance as it learns. Activities, such as playing games and identifying objects, will fall under supervised learning because the computer receives feedback as it reads. Did you guess the object in the picture was right? Did it get the highest score in the game, or lost 10 seconds? Feedback allows it to change its decision-making process so that it can perform better in the future.
  The two most common categories of learning disorders are guarded by fragmentation and learning of resilience. Troubleshooting problem, the system is given input and has to learn how to properly categorize the input, such as an email spam filter or image recognition system.
    In reinforcement learning, the system ("agent") communicates with nature strongly, making decisions for the next sensory function. Depending on the current environment, positive and negative rewards, and actions taken, the agent must learn the best way to accomplish the task.
Examples of machine learning
Machine learning is used to find solutions to various challenges that arise in different contexts and environments. Machine learning as a profession So, it should be obvious now that machine learning is one of the coolest areas of technology — but why should your other child come in and start learning about it?
In the coming years, many companies hope to solve conventional artificial intelligence, which is the name of AI that can learn and perform any task put in front of it. This outbreak may be years ahead, but it has the potential to change the way people interact with technology, the job market, and the wider society.
    In the short term, machine learning has useful business applications such as analyzing more data, more powerful vehicles, and facilitating medical diagnostics. As AI research improves, the number of tasks it can perform will only increase. Companies are already aspiring to AI experts and are hiring for knowledgeable professionals in the field.

Best Online Artificial Intelligence Courses

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, 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 learning to jump straight in the start, those having little exposure could select or opt for those modules which attract them most, whereas machine-learning experts could utilize this as an introduction to TensorFlow.

Google Machine Learning

Google-Machine Learning is 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 focussed on deep learning and the models of auto-teaching systems that can learn from large, complex datasets.

This course has been designed looking forward to putting 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 nowadays in abundance from varied sources and it has been observed that there is an increase in demand in the different 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 to program for some of the assignments. If the students have done introductory courses on probability theory and linear algebra it would be helpful. We will review some of the basic topics in the first two weeks as well.