COMPUTER SCIENCE AND ENGINEERING (AI & ML)

HOD’s Message
Vision Mission
Program
Faculty

“Learn from yesterday, live for today, hope for tomorrow. The important thing is not to stop questioning.” -Albert Einstein

“Arise, awake, and stop not till the goal is reached.” -Swamy Vivekananda

Artificial Intelligence and machine Learning (AI&ML) is a new, emerging field which consists of a set of tools and techniques used to extract useful information from data. Although is in the adoption stage in our country, but it has enormous potential to be utilized in various industries to solve complex problems. The major industries using Artificial Intelligence (AI) and Machine Learning (ML) include Agriculture, Education and Infrastructure, Healthcare, Transport, Banking, Cyber Security, Manufacturing, Entertainment, Hospitality and others.

The ability of a computer-controlled system to perform tasks that are mainly associated with human beings is called Artificial Intelligence (AI). The AI is a simulation of a machine’s natural intelligence that is programmed for communicating and learning human actions. They can perform human-like task and technologies merging with AI is continuing to grow.

Machine learning is a part of Artificial Intelligence that allows software applications in becoming more accurate at predicting outcomes without the need of being explicitly programmed. The machine learning algorithms utilize historical data as an input for predicting recent output values. Machine learning is crucial as it gives the enterprise a correct view of recent trends in business operation patterns and customer behaviour that supports the development of a new product.

The organisation Narula Institute of Technology (NiT) with a pool of distinguished faculties ensure a wide range of diverse learning experiences at both the undergraduate levels, with B.Tech. ranging from the fundamentals of Computer Science, Core Courses, Programming, Emerging Technologies like Big Data Analytics, Data Mining, Pattern Recognition, IoT, AI, Machine Learning, Cyber Security, Blockchain, Professional Ethics, Research Methodologies, and Open-Source Technologies—to name just a few. Department of AI & ML has started its UG program B.Tech. CSE (AI& ML) with 120 intakes.

Narula Institute of Technology has had the honour of having a host of Multinational Companies visit the campus be it, Infosys, ITC-Infotech, TCS, Capgemini, Cognizant, Deloitte, Wipro, IBM, BYJU’S, Accenture just to name a few. Our close industry connections with these organizations ensure better job opportunities for our students through the campus placement drives with astounding packages creating a niche in the professional world.

We welcome students to be the part of Narula Institute of Technology to experience a new journey for a successful engineering career.

Dr. Sagarika Chowdhury
Head, Dept. of AI & ML, Narula Institute of Technology

Faculty Details

Vision

Vision of the Department:

To be an excellent centre for education in the field of Artificial Intelligence and Machine Learning with an aim to produce competent students with a strong theoretical and practical background, suitable for industries and research with social responsibilities.

Mission

Mission of the department:

DM1: Development of models capable of learning from a knowledge-base and storing the acquired knowledge in terms of few learnable model parameters.
DM2: Designing algorithms to optimally estimate model parameters based on suitable criteria and making use of these learnable model parameters for accurate predictions.
DM3: Mould students to be technically competent for analysing data.
DM4: Preparing students for successful professional careers in industry, academics and as an entrepreneur to the nation as a good human being.

Program Educational Objectives (PEOs) (B.Tech.):

PEO1: Graduates are prepared to be employed in IT industries and be engaged in learning, understanding, and applying new ideas.
PEO2: Graduates are prepared to take up Masters / Research programs.
PEO3: Graduates are prepared to be responsible computing professionals in their own area of interest.
PEO4: Graduates are prepared to be good entrepreneur and responsible social representatives.

Program Outcome (POs) (B.Tech.):

PO1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO2. Problem analysis: Identify, formulate, review research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PO3. 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 the public health and safety, and the cultural, societal, and environmental considerations.
PO4. 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.
PO5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.
PO6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
PO7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
PO8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO10. 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.
PO11. 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.
PO12. 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.

Program Specific Outcomes (PSOs) (B.Tech.):

PSO1. Apply the knowledge of data analytics to extract suitable features to represent patterns.
PSO2. Developing models to categorise patterns into appropriate its class.
PSO3. Developing models and algorithms for time-series / sequential data analysis for accurate future output prediction.

	Course Name	Degree	Intake Strength
Under Graduate (UG)	4 years B.Tech Computer Science and Engineering (AI&ML)	B.Tech	120

Students Details