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The B.Tech. CSE (Artificial Intelligence and Data Science) programme is a four year undergraduate course designed to prepare students for the data-driven and intelligent technology landscape. The programme integrates computer science with artificial intelligence, machine learning, and data science to enable the development of smart, predictive, and data-centric solutions.
The curriculum covers key areas such as programming, data structures, artificial intelligence, machine learning, deep learning, big data analytics, and data visualization. Students gain hands-on experience through laboratories, real-time projects, internships, and research activities. The programme emphasizes analytical thinking, problem-solving, and innovation to address real-world challenges across industries.
Strong foundation in computer science, AI, and data science
Focus on machine learning, deep learning, big data, and analytics
Hands-on, project-based, and experiential learning approach
Modern labs with AI and data analytics tools
Internship, industry collaboration, and research opportunities
Emphasis on problem-solving, innovation, and design thinking
Flexible electives in emerging AI and data-driven technologies
Skill development aligned with industry and future technology trends
Graduates of this programme are well-equipped for high-demand roles across IT, finance, healthcare, e-commerce, consulting, and research domains.
Career Roles Include:
Data Scientist
Machine Learning Engineer
AI Engineer
Data Analyst
Business Intelligence Analyst
AI Researcher
The programme also provides a strong foundation for higher studies and research in artificial intelligence, data science, and related fields.
The B.Tech. in Computer Science and Engineering (Artificial Intelligence and Data Science) is a four-year program divided into eight semesters, comprising a total of 160 credits. The curriculum includes a balanced mix of core courses, electives, laboratory work, and project-based learning, designed to progressively build students’ technical knowledge and practical skills.
Semesters 1 & 2: Foundation Category: Provide a strong foundation in mathematics and basic sciences, enabling analytical thinking and problem-solving essential for AI and data-driven applications. It integrates fundamental concepts of electrical, electronics, and mechanical engineering to support interdisciplinary understanding. Students also develop programming skills for problem solving using structured and algorithmic approaches. Additionally, communication skills prepare students for effective collaboration and professional practice in AI and data science domains.
Semesters 3 & 4: Core Computing Category: Builds core computing knowledge through data structures, algorithms, and object-oriented programming for efficient software development. Covers computer organization and operating systems to understand system-level operations, along with database management systems for handling structured data. Discrete mathematics and probability provide the mathematical foundation essential for algorithm design, data analysis, and AI-driven applications.
Semesters 5 & 6: AI & Data Science Core Category: Focuses on advanced AI and data-driven technologies, including artificial intelligence, machine learning, deep learning, and data analytics. It covers big data technologies and data visualization for extracting and presenting meaningful insights from large datasets. Students gain practical experience through mini projects, internships, and skill development activities, preparing them to build intelligent and scalable real-world solutions.
Semesters 7 & 8: Advanced & Specialization Category : Focuses on advanced AI techniques and intelligent systems, including natural language processing and computer vision for real-world applications. Students explore emerging technologies through professional electives and gain practical industry exposure via internships and training. The programme culminates in a capstone project enabling students to develop innovative, data-driven solutions to complex real-world problems.
Candidates seeking admission to the B.Tech. programs must have successfully completed their 10+2 / Intermediate or equivalent examination from a recognized board with Physics, Mathematics, and Chemistry (or relevant subjects), securing a minimum of 60% aggregate marks in the qualifying examination.
Admissions will be based on merit in the qualifying examination and/or performance in recognized national or state-level entrance examinations, such as Joint Entrance Examination (JEE) or relevant State Common Entrance Tests, as per the admission guidelines of the University.
| 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 | $5000 |
| Hostel Fees (Includes Room & Mess Charges) |
$2500 |
| Caution Deposit (Refundable at the End of the Course or After Graduation) |
$400 |
Note:
Hostel stay is Mandatory for students and fees are subject to revision every year
Refund Rules:
Fee refund & cancellation policy will be as per guidelines published by UGC/Statutory authorities.
Note:
Dates and schedules are subject to change.
Kaveri University was established as per the Telangana Private Universities (Establishment & Regulation) Act, 2018 under section 3.
