Programme structure
Undergraduate
Level
4 Years
Duration
₹ 225K / ₹ 300K
Merit / Management Fee
60% marks
Sr. Secondary (10+2)
BrochureOverview
The Department of Artificial Intelligence and Data Science at Kishkinda University is dedicated to providing quality education, research, and innovation in the fields of Artificial Intelligence, Machine Learning, Data Analytics, and intelligent computing technologies. The department aims to develop skilled professionals capable of solving real-world challenges using data-driven and AI-based solutions.
The department focuses on building strong foundations in programming, data analysis, intelligent systems, predictive modeling, cloud technologies, and advanced computing applications. The curriculum integrates theoretical knowledge with practical learning through laboratory sessions, projects, internships, workshops, hackathons, and industry interaction.The department emphasizes emerging technologies such as Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Big Data Analytics, Natural Language Processing, Computer Vision, Cloud Computing, Cyber Security, and Internet of Things (IoT). Students are encouraged to participate in research activities, innovation projects, technical competitions, and industry-oriented training programs.
With experienced faculty members, modern laboratories, smart classrooms, and technology-enabled learning environments, the department prepares students for successful careers in software industries, research organizations, analytics companies, startups, and higher education.
Eligibility
10+2 with Physics & Mathematics + Chemistry / CS / BiologyStudents who have passed BiPC, PCMB, PCB and any one from Physics, Chemistry, Biotechnology & Maths with English as one of the languages of study and should have obtained a minimum of 45% marks.For SC/ST & Other backward classes of Karnataka students only, the minimum marks is 40% in aggregate in the optional subjects in the qualifying examination like CET / Comed-K / AIEEE any other equivalent entrance examinations
Teaching Pedagogies
The Computer Science and Engineering (Artificial Intelligence & Data Science) program at Kishkinda University adopts innovative, technology-driven, and industry-oriented teaching pedagogies to develop students’ expertise in intelligent systems, data-driven technologies, and advanced computing applications. The program combines theoretical learning with practical implementation to prepare students for emerging careers in AI, Machine Learning, Data Science, and automation technologies.
- Interactive Classroom Teaching
- Project-Based Learning
- Experiential Learning
- Outcome-Based Education (OBE)
- Case Study and Problem-Solving Methods
- Industry Interaction and Expert Sessions
- Collaborative Learning and Team Projects
- Research and Innovation-Oriented Learning
- Continuous Evaluation and Skill Assessments
Interactive Classroom Teaching
Interactive Classroom Teaching
Concept-oriented lectures using smart boards, multimedia presentations, AI demonstrations, and active classroom discussions to improve conceptual understanding.
Project-Based Learning
Experiential Learning
Outcome-Based Education (OBE)
Case Study and Problem-Solving Methods
Industry Interaction and Expert Sessions
Collaborative Learning and Team Projects
Research and Innovation-Oriented Learning
Continuous Evaluation and Skill Assessments
The department emphasizes emerging technologies such as Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Natural Language Processing, Computer Vision, Robotics, Cloud Computing, and Internet of Things (IoT).
Specialization
Artificial Intelligence
Development of intelligent systems capable of learning, reasoning, and decision-making.
Data Science and Analytics
Collection, processing, visualization, and analysis of structured and unstructured data
Deep Learning
Advanced neural network techniques for image recognition, speech processing, and AI applications.
Big Data Analytics
Processing and analysis of large-scale datasets using modern analytical technologies.
Natural Language Processing (NLP)
Development of systems capable of understanding and processing human language.
Computer Vision
AI techniques for image processing, object detection, and visual data interpretation.
Predictive Analytics
Forecasting future trends and outcomes using statistical and analytical models.
Cloud Computing
Cloud-based data storage, processing, and deployment of AI applications.
Internet of Things (IoT)
Development of smart connected systems integrated with AI and data analytics.
Cyber Security and Data Protection
Security techniques for protecting digital systems and sensitive information.
Robotics and Intelligent Automation
Development of automated systems and smart robotic technologies.
Data Visualization Techniques
Representation of data through dashboards, charts, and visual analytical tools.
AI-Based Application Development
Design and development of intelligent software applications and smart systems.
Program Educational Objectives (PEOs)
PEO - 1
Graduates will apply Artificial Intelligence, Data Science, and analytical techniques to derive meaningful insights and develop data-driven solutions for real-world industrial and societal applications.
PEO - 2
Graduates will exhibit professional competence, innovation, critical thinking, leadership, and entrepreneurial abilities in areas related to intelligent systems, analytics, research, and emerging technologies.
PEO - 3
Graduates will pursue lifelong learning, ethical computing practices, and interdisciplinary research to contribute towards sustainable technological advancement and community development.
Program Outcomes (PO)
PO - 1
Engineering Knowledge: Apply principles of mathematics, natural sciences, computing, engineering fundamentals, and specialized engineering knowledge to develop solutions for complex engineering problems.
PO - 2
Problem Analysis: Identify, formulate, and analyse complex engineering problems by reviewing research literature and drawing well-founded conclusions, while considering sustainable development.
PO - 3
Design/Development of Solutions: Design innovative solutions for complex engineering problems and develop systems, components, or processes that address identified needs, considering public health and safety, whole-life cost, net-zero carbon goals, culture, society, and environmental impact.
PO - 4
Conduct Investigations of Complex Problems: Utilize research-based knowledge to investigate complex engineering problems, incorporating experiment design, modelling, data analysis, and interpretation to derive valid conclusions.
PO - 5
Engineering Tool Usage: Develop, select, and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, while recognizing their limitations in solving complex engineering problems.
PO - 6
The Engineer and the World: Assess and evaluate societal and environmental factors when addressing complex engineering problems, considering their impact on sustainability in relation to the economy, health, safety, legal frameworks, culture, and the environment.
PO - 7
Ethics: Uphold ethical principles, demonstrate commitment to professional integrity, respect human values, and promote diversity and inclusion while adhering to national and international laws.
PO - 8
Individual and Team Collaboration: Work effectively both independently and as a member or leader in diverse, multidisciplinary teams.
PO - 9
Communication: Communicate clearly and inclusively within the engineering community and society, demonstrating the ability to write effective reports, develop design documentation, and deliver impactful presentations while considering cultural, language, and learning differences.
PO - 10
Project Management and Finance: Apply engineering management principles and economic decision-making to one’s work, effectively managing projects and contributing as both a team member and leader in multidisciplinary environments.
PO - 11
Life-Long Learning: Acknowledge the importance of continuous learning and cultivate the skills necessary for:
i) Independent and sustained self-improvement,
ii) Adaptability to evolving and emerging technologies, and
iii) Critical thinking in the broader landscape of technological advancements.
Program Specific Outcomes (PSO)
PSO - 1
Apply Artificial Intelligence, Data Science, and analytical techniques to process, analyze, and interpret complex datasets for intelligent decision-making and problem-solving.
PSO - 2
Design and develop data-driven applications using Machine Learning, Big Data technologies, cloud platforms, and visualization tools for industrial and societal applications.
PSO - 3
Demonstrate innovation, research orientation, ethical computing practices, and professional skills to contribute effectively in multidisciplinary environments, entrepreneurship, and advanced technology domains.
Scholarship
Kishkinda University supports eligible students in availing Government Scholarships through recognized portals such as SSP (State Scholarship Portal) and NSP (National Scholarship Portal). Students who meet the eligibility criteria can apply directly through these official portals and complete the scholarship process as per government guidelines.
Available Scholarship Portals
SSP – State Scholarship Portal
For students eligible under Karnataka State Government scholarship schemes.
NSP – National Scholarship Portal
For Central Government scholarship schemes applicable across India.
How to Apply
-
01
Visit the official SSP or NSP portal.
-
02
Register with required academic and personal details.
-
03
Upload necessary documents (income certificate, caste certificate, marks cards, Aadhaar, etc.)
-
04
Submit the application online within the specified deadline.
-
05
Submit acknowledgment copy to the University Scholarship/Accounts Section (if required).
Career Prospects
Core Career Opportunities
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- Data Analyst
- Software Developer (AI-based Applications)
Emerging Technology Domains
- Artificial Intelligence and Deep Learning
- Natural Language Processing (NLP)
- Computer Vision
- Robotics and Intelligent Systems
- Generative AI and Automation
Industry and Employment Opportunities
- IT and Product-based Companies
- AI-focused Startups
- Healthcare, Finance, and E-commerce Industries
- Research and Development Organizations
- Government and Smart Technology Projects
Higher Studies and Research
- M.Tech / MS in AI, Data Science, Machine Learning
- MBA (Analytics / Technology Management)
- PhD and Advanced Research
- Industry Certifications (AI, Cloud, Data Science)
Entrepreneurship and Other Paths
- AI-based Startups and Innovation
- Freelancing in Data Science and AI Projects
- Technical Blogging and Content Creation
- Teaching and Academia
FAQ's
It is a specialized program focusing on Artificial Intelligence, Data Science, analytics, and intelligent computing technologies.
