Artificial Intelligence Engineering Colleges in Delhi NCR

About Department

About AI & ML

Essentially, the B.Tech undergraduate program in Artificial intelligence and machine learning revolves around the programming of machines. In essence, it allows the candidate in communicating to the machine in the machine’s mother tongue. Thus in the program, the candidate is required to learn these specific languages which can be used to customize the function of machines.

This is only one of the many faces of this program, a lot more is taught alongside these rudimentary topics. Many aspects which aid the student in understanding the functioning are taught in this course, for instance information relating to knowledge representation, probabilistic models and reasoning methods are also taught to the candidate form the computer perspective.

The candidates just don’t solely learn about artificial intelligence; they are actually familiarized with more intricate of the decorum. For instance, they are taught about deep learning, human computer interaction and augmented reality.

It is not a new fact, but in recent years with the advent of the internet, a age of automation has also rapidly risen. The requirement of artificial intelligence is skyrocketing. The biggest companies in the global market revolve around programming for instance Facebook, google in foreign player and Wipro among the Indian IT companies may hire individuals who are passed out form this undergraduate course. Thus this may provide ample opportunity to the graduate once he steps into the service sector.

BTech Artificial Intelligence and Machine Learning at a Glance:

The global market since the advent of the internet and smartphones have been leaning towards artificial intelligence. In the current automated age machines are required for successfully completing numerous tasks, lives of individuals in the current world are to an extent dependent on proper functioning of these machines.

The market share of artificial intelligence is projected to grow USD 190.61 Billion by 2025.
Ai in the current world is omnipresent; it has made its way in the service sectors on numerous levels.
In the current automated world, it is quite rare to find a sector or horizon untouched by AI.

Thus pursuing this field will enable the individuals in obtaining these highly favourable jobs which are only bound to increase with time.

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Programme Outcomes

Programme Outcomes (POs)

Computer Science Engineering graduates will be able to:

Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
Problem analysis: Identity, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using the first principles of mathematics, natural sciences, and engineering sciences.
Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for public health and safety, and cultural, societal, and environmental considerations.
Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
The engineer and society: Apply reason informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
Environment and sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.