The student selected for theBNY Mellon Internship 2025 secured
2nd place at the national level in the
same challenge and was awarded a cash prize of ₹45,000.
2 Students got qualified in GATE-2025
Student secured an onsite internship at Symphonize in the field of
Intelligence and Machine Learning, with a stipend of ₹30,000 for the entire duration.
6 students selected for the IASc-INSA-NASI Summer Research Fellowship 2025.
B.Tech in Computer Science and Engineering (Artificial Intelligence and
Machine Learning) is a four-year
undergraduate
program that started
with an intake of 60 in 2022 and combines the study of traditional computer science with
the principles and
techniques of data science.
The program typically covers a broad range of topics in computer science, including data
structures,
algorithms, problem-solving techniques, programming languages, operating systems, and
computer networks.
In addition, the program may include courses on Data Science and Machine Learning (ML)
topics such as
statistical analysis, data visualization, database systems, data mining, data analytics,
big data technologies, machine learning algorithms, business intelligence, and more.
Graduates of this program may work in various industries, including technology, finance,
healthcare, retail, transportation, manufacturing, energy, agriculture, marketing,
cyber-security, government and more. Opportunities like data scientists, machine
learning engineers, business intelligence analysts, data engineers, software developers,
or other roles involve designing and implementing intelligent systems. They may also
pursue further studies in post-graduate programs in Data Science, AI, ML or related
fields.
Some of the industries where data scientists are in high demand include:
Technology: Technology companies, such as Facebook, Apple, Amazon, Netflix,
Google,
and other top tech companies, hire data scientists to work on various projects,
including search algorithms, advertising systems, and recommendation engines.
Finance: Financial institutions such as banks, hedge funds, and insurance
companies
use data science to support decision-making, detect fraud, predict customer
behaviour and develop new financial products.
Healthcare: Data scientists in healthcare are working on areas such as
precision medicine, drug development, patient outcomes analysis, and medical imaging
analysis.
Retail: Retail companies use data science to analyze customer behaviour and
sales data to improve marketing and inventory management, forecast demand and
optimize pricing.
Manufacturing and Automotive: Companies in these industries use data science
for predictive maintenance, quality control and optimizing their supply chains
Energy and utilities: Companies in this field use data science to optimize
power generation, transmission, and distribution.
Consulting: Data Science consulting companies work with clients from diverse
fields, helping them to leverage data to improve their business operations and
strategies.
Government and non-profit:Data science is also applied in government and
non-profit organizations for areas like policy-making, budget allocation and public
welfare.
Media and Advertising: Companies in media and advertising use data science to
understand customer preferences and make better ad placement and targeting
decisions.
Cyber security: Companies and organizations that provide cyber security
solutions use data science techniques to protect against data breaches,
cyber-attacks and data theft.
To provide rich ambience for Academic and Professional Excellence, Research, Employ
-
ability skills, Entrepreneurship, and Social responsibility.
To empower the students with technical knowledge, Awareness of up-to-date technical
trends, Inclination for research in the areas of human needs, Capacity building for
Employment / Entrepreneurship, and Application of technology for societal needs.
PROGRAM OUTCOMES (POs)
PO-1
Engineering Knowledge:
Apply the knowledge of mathematics, science, engineering
fundamentals, and an engineering specialization to the solution of complex
engineering problems.
PO-2
Problem Analysis:
Identify, formulate, review research literature, and analyze complex engineering
problems reaching substantiated conclusions using first principles of mathematics,
natural sciences and engineering sciences.
PO-3
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.
PO-4
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.
PO-5
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.
PO-6
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.
PO-7
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.
PO-8
Ethics:
Apply ethical principles and commit to professional ethics and responsibilities and
norms of the engineering practice.
PO-9
Individual and Team Work:
Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO-10
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.
PO-11
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.
PO-12
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 EDUCTIONAL OUTCOMES (PEOs)
PEO-1
The graduates of the program will excel in the concepts of basic engineering and advanced
concepts of computer science engineering.
PEO-2
The graduates of the program will be professional in computing industry or pursuing higher
studies.
PEO-3
The graduates of the program will excel in team work, ethics, communication skills and contribute
to the benefit to the society.
PROGRAM SPECIFIC OUTCOMES (PEOs)
PSO-1
Apply the Knowledge of Computing Skills in building the Software Systems that meet the
requirements of Industry and Society.
PSO-2
Apply the Knowledge of Data Engineering and Communication Technologies for Developing
Applications in the Domain of Smart and Intelligent Computing.
Facilities (Our Assets)
Application Development
Design and develop modern applications. Focus on full-stack
development.
Programming Languages Lab
Master various programming paradigms. Enhance coding
efficiency.
Data Visualization Tools
Turn data into insights with visuals. Learn tools like
Tableau and Power BI.
Deep Learning Lab
Focus on neural networks and AI. Work on real-world AI
projects.
NLP Lab
Explore natural language processing. Build intelligent
language models.
Database Systems Lab
Learn database design and management. Master SQL and NoSQL
systems.
Skill Development
Collaborate on innovative team projects. Enhance
problem-solving skills.
Full Stack Web Development
Build responsive websites and web applications using modern
technologies.