Eligibility For B.Tech. Programme

• Candidates should have passed 12th standard examination conducted by State Board / CBSE / ISC or equivalent examination with a minimum aggregate of 50% marks in Physics, Chemistry and Mathematics.
• Candidates should have appeared for the Crescent Institute Engineering Admission Test (CIEAT 2025) or should have a valid score in JEE (Main).
• Candidates who have studied in Regular, Full time and Formal Education alone are eligible to apply.
• Age Limit: The date of birth should be between January 2003 and December 2008.

CIEAT 2025 – Crescent Institute Engineering Admission Test

Selection Process
Candidates will be selected for admission to B.Tech. Programme of all branches of study based on the merit in the qualifying examination and the marks scored in the Crescent Institute Engineering Admission Test (CIEAT 2025). Candidates having a valid score in JEE (Main) will be directly selected for admission.

CIEAT-2025 is an all India level Admission Test conducted for selecting the candidates for admission to B.Tech. Programmes.

CIEAT – 2025 will be conducted through Proctored Online Mode.
Date of Test : 26th April 2025

Applications are invited from prospective Candidates.

For Assistance
Help Desk : +91 95432 77888
e-mail : admissions@crescent.education

Admission Brochure 

Programme Educational Objectives

• To introduce the fundamentals of science and engineering concepts essential for a data architect / data scientist
• To inculcate the knowledge of mathematical foundations and algorithmic principles for effective problem solving
• To provide knowledge in data sciencefor modern computational data analysis and modeling methodologies
• To provide the knowledge in artificial intelligence techniquesand apply them to develop relevant models and real time products
• To impart knowledge to analyze, design, test and implement the model required for various applications
• To hone personality skills, trigger social commitment and inculcate societal responsibilities

Programme Outcomes

• Analyse and build models applying the knowledge of mathematics, statistics, electronic, electrical and computer science discipline and solve the problem
• Identify the sources of information for data collection, design and conduct the experiments and interpret the result
• Think out-of-the box and solve the real time problems using their creativity in designing human friendly software systems
• Comprehend computer engineering concepts of the new research developments and apply them to develop relevant software and hardware products
• 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
• Apply the computing knowledge to solve the socially relevant problems
• Understand the impact of engineering solutions in global, economic, environmental, societal context and apply it in exploring the new developments, research trends and involve them in research
• Develop professional integrity by understanding and appreciating professional, legal, ethical, cyber security and related issues and act with responsibility
• Communicate, collaborate and work as a team by involving in the group projects of multi-disciplinary nature
• To prepare documents as per the standards and present effectively to improve software documentation skills
• Apply the hardware and software project management techniques to estimate the time and human resources required to complete computer engineering projects
• 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

Programme Specific Outcomes

• Understand, analyze and develop essential proficiency in the areas related to data science and artificial intelligence in terms of underlying statistical and computational principlesand apply the knowledge to solve practical problems
• Implement Artificial Intelligence and data science techniques such as search algorithms, neural networks, machine learning and data analytics for solving a problem and designing novel algorithms for successful career and entrepreneurship

Click here for Detailed Syllabus