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Program Details
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UndergraduatePROGRAMME LEVEL
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EnglishLANGUAGE
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4YEAR PROGRAM
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8SEMESTER
About the Program
The B.Tech. in Computer Science and Engineering (Machine Learning) at Sanskaram University is an undergraduate program dedicated to the study and application of machine learning technologies. The curriculum includes core computer science subjects alongside specialized courses in algorithms, data mining, statistical analysis, and neural networks. Emphasizing experiential learning, the program incorporates practical labs, projects, and internships, enabling students to develop robust machine learning models and applications. Graduates are equipped with the expertise needed to pursue careers in machine learning across various industries, driving innovation and efficiency.
Eligibility
Candidate should have passed 10+2 examination conducted by CBSE or equivalent examination from a recognized board with Physics, Mathematics as compulsory subjects along with one of the following subjects i.e. CS/Chemistry/Biotech with a minimum 45% marks in aggregate.
Fee Structure
| Program Fees (Per Annum) | 1,90,000 | |
| Security Fees (One Time, Refundable) | 10000 | |
| Prospectus (One Time, Non Refundable) | 1000 | |
| Alumni Fees (One Time, Non Refundable) | 2000 |
Program Outcomes
Engineering Knowledge Apply knowledge of mathematics, computer science principles, machine learning algorithms, and engineering fundamentals to develop and implement machine learning solutions.
Problem Analysis Identify, formulate, and analyze complex machine learning problems, and develop effective solutions by using appropriate mathematical models, algorithms, and data analysis techniques.
Design and Development of Solutions Design and develop machine learning systems and applications that meet specified requirements, ensuring accuracy, scalability, and efficiency while addressing real-world challenges
Modern Tool Usage Select and apply appropriate software tools, programming languages, and machine learning frameworks to design, build, and evaluate machine learning models effectively.
Individual and Team Work Function effectively as an individual and as part of a multidisciplinary team, collaborating on machine learning projects and contributing to innovative solutions in both academic and professional settings
Program Educational Objectives
Strong Foundation in Computer Science and Machine Learning Graduates will possess a solid understanding of computer science fundamentals, algorithms, data structures, and core machine learning principles, enabling them to solve complex problems using machine learning techniques.
Expertise in Machine Learning Algorithms and Applications Graduates will demonstrate proficiency in designing, developing, and deploying machine learning models, utilizing advanced algorithms, statistical methods, data mining, and neural networks for real-world applications across diverse industries.
Problem Solving and Innovation Graduates will apply their knowledge of machine learning and data science to innovate and create efficient, scalable solutions for complex problems in fields such as healthcare, finance, robotics, and autonomous systems.
Professionalism and Ethical Responsibility Graduates will be equipped with the necessary skills to demonstrate professionalism, adhere to ethical standards, and engage in continuous learning, while working on machine learning projects that respect privacy, fairness, and transparency.
