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B. Tech. in Information Technology – Data Analytics (IBM)

Overview

This programme prepares students to excel in the dynamic field of data analytics by combining a solid IT foundation with courses focused on the principles, tools, and data analysis techniques. Students are equipped to make data-driven decisions and contribute to the evolving IT landscape.

The curriculum covers various topics and prepares students to excel in the dynamic field of data analytics. It combines a strong IT foundation with courses focused on the principles, tools, and techniques of data analysis.

This is essential for working effectively with data, ensuring students are well-prepared to meet industry demands and offering an industry-aligned curriculum that meets professional standards, emphasising practical application in real-time problem-solving using Al and ML.

Duration

B. Tech. (Regular): Four Years / Eight Semesters

B. Tech. (Lateral): Three Years / Six Semesters

Commence of the course


Course Duration

Four Years


Mode of Study

Eligibility


For Regular

10+2 from recognized Board / Council with Minimum 50% marks in Physics & Mathematics as compulsory subjects along with one of the Chemistry / Biotechnology / Biology / Technical Vocational Subject.

Score in JEE (Main); JEE (Advanced); Karnataka CET; COMED-K; AUEET (Alliance Undergraduate Engineering Entrance Test); or any other State-Level engineering entrance examination.


For Lateral Entry

Passed Diploma examination with at least 50% marks in relevant branch of Engineering and Technology.

Passed B. Sc. Degree from a recognized University as defined by UGC, with at least 50% marks & passed 10+2 examination with Mathematics as a subject.

A relaxation of 5% marks or its equivalent grade may be allowed for those belonging to SC / ST.


Programme Features

Certifications are offered through MoUs by reputable organisations.

Advanced lab facilities featuring centres of excellence with Apple and CoE.

Hands-on experience in real-time problem-solving using Al and ML.

Focus on innovation, operational efficiency, and enterprise data optimisation.

Skill certifications from platforms like Google and Meta via Coursera.

Access to high-performance computing units for large-scale data processing.

Training in recent trends and repositories in data analytics tools.

Programme Structure

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