Posted on 3rd Jun 2021 05:39:18 in

 B.Tech CSE with specialization in Artificial Intelligence and Machine Learning

“Predicting the future isn’t magic, it’s artificial intelligence.” – Dave Waters

Artificial Intelligence and Machine Learning (AI and ML) has transformed our lives. We can’t even think of a day when some sort of AI technology is not assisting us. From spam filters and smart replies in Gmail to mobile banking, Google maps Siri, Alexa, Autonomous Cars , Robotic Vaccum to name a few. AI and ML has not left even a single stone unturned to reach where it is at the moment. Automation that is enhanced through artificial intelligence (AI) is critical to organizations’ ability to compete and survive in the years ahead, according to nearly 400 business leaders recently surveyed by Harvard Business Review. Artificial intelligence isn’t just a prevailing fashion. It’s setting down deep roots. There is an increasing need for intelligent and accurate decision-making across industries. This has led to an exponential growth in the adoption of AI and ML technologies which is likely to remain prevalent in the years to come. By the year 2022 AI-ML market size is likey to $8.81 billion. And, this means that industry will surely need a skilled workforce to build, test and deploy more and more artificial brains around the world. This will help change the world. If you are interested in a career in artificial intelligence, then you’re in the right place. A career in artificial intelligence has variety of fields including private companies, public organizations, education, healthcare facilities, government agencies and the military.

Learning outcomes of this track:

• To Understand and implement search and adversarial (game) algorithms
• To formulate mathematical models such as belief networks and Markov decision methods in the data driven decision making.
• To explore supervised, unsupervised and reinforcement learning and apply them to a range of AI problems.
• To understand the probabilistic foundations and learning algorithms for deep neuralnetworks models.
• To learn and implement the basic methodologies and tools in robotics research and applications
• To explore the fundamental concepts of NLP and its role in current and emerging technologies.