Programme structure
Undergraduate
Level
4 Years
Duration
₹ 225K / ₹ 300K
Merit / Management Fee
60% marks
Sr. Secondary (10+2)
BrochureOverview
The Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning) focuses on excellence in teaching, research, and innovation in intelligent computing technologies. The department aims to develop skilled professionals with strong foundations in programming, data science, and machine learning, along with practical expertise to meet the growing demand for AI-driven solutions.
The curriculum integrates theoretical concepts with hands-on learning through labs, projects, and industry exposure. Students are trained to build intelligent systems, predictive models, and data-driven applications, enhancing their problem-solving and analytical abilities.
The department emphasizes emerging areas such as Artificial Intelligence, Deep Learning, Natural Language Processing, Computer Vision, and Big Data Analytics. With modern labs, experienced faculty, and industry interaction, the department prepares students to become industry-ready professionals and innovators in AI technologies.
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 & Machine Learning) 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 decision-making and automation.
Machine Learning
Design of algorithms that enable systems to learn from data and improve performance.
Deep Learning
Advanced neural network techniques for image recognition, speech processing, and AI applications.
Data Science and Analytics
Collection, processing, and analysis of large datasets for business and technological insights.
Natural Language Processing (NLP)
Development of systems that understand and process human language.
Computer Vision
AI techniques for image processing, object detection, and visual data interpretation.
Robotics and Intelligent Automation
Development of smart robotic systems and automation technologies.
Big Data Technologies
Processing and management of large-scale structured and unstructured data.
Cloud Computing for AI
Cloud-based deployment and management of AI and ML applications.
Cyber Security and AI Security
Protection of intelligent systems and digital infrastructure from cyber threats.
Internet of Things (IoT)
Development of smart connected systems integrated with AI technologies.
Predictive Analytics
Data-driven forecasting and intelligent decision-making techniques.
Business Intelligence
Use of AI and analytics for organizational decision-making and strategic planning.
AI-Based Application Development
Design and development of intelligent software applications and smart systems.
Ethical AI and Responsible Computing
Understanding ethical practices, fairness, and responsible use of AI technologies.
Program Educational Objectives (PEOs)
PEO - 1
Graduates will develop innovative AI and Machine Learning solutions addressing regional, industrial, agricultural, healthcare, and societal challenges through sustainable and technology-driven approaches.
PEO - 2
Graduates will demonstrate strong technical competence, leadership, entrepreneurship, and collaborative skills to contribute effectively in multidisciplinary environments, research, startups, and global industries
PEO - 3
Graduates will engage in lifelong learning, ethical AI practices, and continuous innovation to adapt to emerging technologies and support digital transformation with social responsibility.
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, Machine Learning, and Deep Learning techniques to design intelligent systems and solve real-world problems in domains such as healthcare, agriculture, business, and automation.
PSO - 2
Develop innovative software solutions using modern tools, programming platforms, cloud technologies, and data-driven approaches for intelligent computing applications.
PSO - 3
Demonstrate research aptitude, ethical practices, teamwork, and entrepreneurial skills to contribute effectively in industry, higher education, and emerging technology sectors.
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, Machine Learning, and data-driven technologies.
