The B.Tech. Computer Science and Engineering (Data Science) is a 4-year undergraduate programme designed to equip students with the ability to extract meaningful insights from data using machine learning techniques, algorithms, statistical tools, and domain understanding. The programme blends technology, analytical thinking, and data inference to solve complex real-world problems.
The curriculum integrates business knowledge, computational skills, and statistical methods to help students generate innovative data-driven solutions. It covers key areas such as Basic Sciences, Mathematical and Statistical Foundations, Artificial Intelligence, Machine Learning, Data Science, Deep Learning, and Data Visualization.
The programme emphasizes design thinking, communication, collaboration, and creativity from the first year and offers flexibility through a wide range of foundation, professional, and elective courses.
Interdisciplinary Curriculum:Combines computer science, mathematics, statistics, and emerging AI technologies with electives from fields such as agriculture, healthcare, fintech, and automation.
Industry-Aligned Content:Designed in consultation with industry partners and aligned with frameworks like NASSCOM Future Skills and AICTE Model Curriculum.
Hands-on Learning:Project-based pedagogy, lab-intensive courses, and real-world problem-solving using Python, TensorFlow, PyTorch, and cloud platforms.
Capstone Projects & Internships: Mandatory industry internship and a final-year capstone project in collaboration with startups or corporate R&D units.
AI &AgriTech Integration: Unique opportunity to apply AI to agriculture and sustainability domains in line with Kaveri University’s core strengths.
Global Readiness: Courses on Responsible AI, cross-cultural communication, and research exposure to prepare students for international opportunities.
Entrepreneurship Support:Access to the university’s Innovation & Incubation Center for AI-driven startups and product development.
The program aims to:
Develop a strong foundation in computer science, statistics, and mathematics essential for data analysis.
Build competency in machine learning, AI, data mining, and predictive analytics.
Equip students with skills to process, manage, and analyze large-scale structured and unstructured data.
Provide hands-on experience with data science tools, programming languages, and cloud-based analytical platforms.
Enhance problem-solving, critical thinking, and decision-making abilities using data-driven approaches
Foster professional ethics, communication skills, and teamwork for effective participation in multidisciplinary environments.
Prepare students for advanced research, entrepreneurship, or industry roles in data-centric domains.
Graduates can pursue diverse and high-demand careers across IT, finance, healthcare, e-commerce, consulting, and research sectors. Popular career roles include:
Data Scientist
Data Analyst
Machine Learning Engineer
AI Engineer
Business Intelligence Analyst
Data Engineer
Statistician / Research Analyst
Big Data Engineer
Deep Learning Specialist
Product Data Manager
Database Administrator
Quantitative Analyst
Cloud Data Architect
The B.TechCSE(AI & ML) program is structured over eight semesters, comprising a total of 163 credits, and includes a balanced blend of core courses, electives, laboratory work, internships, and a capstone project. The curriculum is designed to progressively build foundational knowledge, domain expertise, and practical skills.
Semesters 1–2: Foundations: Focus on core subjects in Mathematics, Physics, and introductory courses in Computer Science, including programming and data structures, laying the groundwork for AI and ML competencies.
Semesters 3–4: Core Computing Disciplines and AI Fundamentals: Courses in software engineering, database systems, operating systems, machine learning, and artificial intelligence provide a strong theoretical and practical base.
Semesters 5–6: Specializations and Advanced Technologies: Students choose from domain-specific electives in areas such as Advanced Machine Learning, Natural Language Processing, Data Science, Cybersecurity, and Edge/Cloud Computing, enabling in-depth skill development.
Semesters 7–8:Capstone and Emerging Technologies:Emphasis on project-based learning through a capstone project, along with exposure to emerging technologies like Generative AI, Explainable AI, AI in IoT, and Responsible AI.
The program adopts an outcome-based education (OBE) model with flexibility under the Choice Based Credit System (CBCS) and supports credit accumulation through the Academic Bank of Credits (ABC) framework
Qualify in JEE (MAIN) 2025 examination and be eligible to write the JEE Advanced 2025 Or Top All India Rank in JEE (MAIN) 2025 examination (Exact cut off rank would be announced upon declaration of results).
A Valid SAT Subject test Score (which should include Mathematics, Physics, Chemistry) – Minimum 1800
A Valid SAT Test Score – Minimum of 800
A Valid ACT Score – Minimum Composite Score of 18
Note:
| Students Under Indian Category | ₹ Per Annum |
|---|---|
| Academic Fees | ₹ 3,00,000 |
| Hostel Fees (2 Sharing Includes Room & Mess Charges) |
₹ 1,50,000 |
| Hostel Fees (4 Sharing Includes Room & Mess Charges) |
₹ 1,25,000 |
| Caution Deposit (Refundable at the End of the Course or After Graduation) |
₹ 20,000 |
| Students Under NRI/PIO/FO Category | $ USD Per Annum |
|---|---|
| Academic Fees | $3500 |
| Hostel Fees (Includes Room & Mess Charges) |
$2000 |
| Caution Deposit (Refundable at the End of the Course or After Graduation) |
$400 |
Note:
Hostel stay is Mandatory for students andfees are subject to revision every year
Refund Rules:
Fee refund & cancellation policy will be as per guidelines published by UGC/Statutory authorities.
Graduates of this program can pursue careers as:
Kaveri University was established as per the Telangana Private Universities (Establishment & Regulation) Act, 2018 under section 3.
