Introduction
Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. The field of artificial intelligence has been an interdisciplinary endeavor, requiring deep knowledge of both computational and human sciences. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
Advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry. Moreover, the growing impact of AI on society demands that graduates are capable and ethical collaborators, able to ensure the safe and effective adoption of new technologies across domains.
The program begins with introductory courses in programming, computer science, mathematics, and statistics that provide a firm technical foundation. From there, learn core AI concepts and techniques including AI & ML Techniques, Virtual Reality, Web Applications using Machine Learning Techniques, Natural Language and Image Processing, Robotic Process Automation, Business Analytics, Speech Processing, Cognitive systems, Biometrics Systems, computer vision, and language understanding. The program includes a variety of advanced AI electives, enabling technical mastery in specific subfields. Also, specific electives are introduced that will focus on the Application of AI in various industry.
Labs and Practicals
- Data Structures Lab, Algorithms Lab
- Micro-controller and Embedded Systems Lab
- AI and Machine Learning Lab
- Web Applications Lab
- Natural Language and Image Processing Lab
- Mobile Application Development & Robotics Lab
- Internet of Things Lab
Vision
To create well groomed, technically competent and skilled AIML professionals who can become part of industry and undertake quality research at global level to meet societal needs.
Mission
- Provide state of art infrastructure, tools and facilities to make students competent and achieve excellence in education and research.
- Provide a strong theoretical and practical knowledge across the AIML discipline with an emphasis on AI based research and software development.
- Inculcate strong ethical values, professional behaviour and leadership abilities through various curricular, co-curricular training and development activities.
Program Educational Objectives (PEOs)
- Graduates will follow logical, practical and research-oriented approach for solving the real world problems by providing AI based solutions.
- Graduates will work independently as well as in multidisciplinary teams at workplace.
- Graduates will setup start-up and become successful entrepreneurs.
Program Specific Outcomes (PSOs)
The graduates of AIML department will be able to
- Train machine learning models to address real life challenging problems using acquired AI knowledge.
- Develop applications using ML techniques related to the field of medical, agriculture, defence, education and various scientific explorations.
Program Outcomes (POs)
PO1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems
PO2: Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences
PO3: Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations
PO4: Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions
PO5: Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations
PO6: The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice
PO7: Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development
PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice
PO9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings
PO10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions
PO11: Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments
PO12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change
Course Outcomes (COs)
2018 Scheme Click Here
Department Advisory Board
- Mr. Sunil Kumar, Senior Assistant Professor & HoD, Chairperson
- Dr. Prashanth C M, Principal, Member
- Dr. Shreekumar, Associate Professor, CSE
- Mr. Rajesh N. Kamath, Senior Assistant Professor, ISE
- Ms. Radha E G, Assistant Professor, Member
- Ms. Shruthi Kotekar, Adjunct Faculty & Industry Expert, Member
- Dr. Narendra VG, Associate Professor Department of Computer Science & Engineering, MIT, Manipal, Academic Expert
- Ms. Kavyashree Kotekar, Glowtouch Technologies, Mangalore, Industry Expert
- Ms. Prarthana Bhat, CSE-2011, Sr. Data Scientist, GSK, Alumni Representative
Faculty
Dr. Sunil Kumar S.
Educational qualification
B.E – Computer Science and Engineering
M.Tech – Software Engineering
Ph.D in Computer Science and Engineering (Wireless Sensor Networks)
Total experience
10 Years 6 Months
Area of Interest
- IoT
- Data Analytics
Professional Memberships
ISTE
Subjects Handled
- Big Data Analytics
- DBMS
- Computer Network
- Storage Area Network
- Information Network Security
- Data Mining
- Software Engineering
- File Structures
- 8086 Microprocessor
- Wireless Ad Hoc Networks
- C++ Programming
- C# Programming
- Advanced DBMS
- Unix System Programming
- System Simulation & Modelling
Workshops/FDP’S/SDP’S Attended
10
Conference/Journal Publications
- Sunil Kumar S., Aithal G., Venkatramana Bhat P. (2021) Design, Calibration, and Experimental Study of Low-Cost Resistivity-Based Soil Moisture Sensor for Detecting Moisture at Different Depths of a Soil. In: Chiplunkar N., Fukao T. (eds) International Conference on Advances in Artificial Intelligence and Data Engineering (AIDE2019), NMAMIT, Nitte, published in book series “Advances in Intelligent Systems and Computing”, vol 1133. Springer, Singapore. https://doi.org/10.1007/978-981-15-3514-7_104.
- Sunil Kumar S, Nagesh H.R, “WSN based Soil Moisture Stress Monitoring and identifying its association on Other Parameters on plants growth using hadoop Framework,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.51-54, 2016.
- S. G. Kanbargi and Sunil Kumar S, “Cache utilization for enhancing analyzation of Big-Data & increasing the performance of Hadoop,” 2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15), Bangalore, India, 2015, pp. 1-7, doi: 10.1109/ITACT.2015.7492645.
- Sunil Kumar S, Sanjeev G Kanabargi, “Challenges for HDFS to Read and Write Using Different Technologies”, International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SUB154956, Volume 4 Issue 5, May 2015, 2837 – 2842
- S. Pai, Y. Sharma, S. Kumar, R. M. Pai and S. Singh, “Formal Verification of OAuth 2.0 Using Alloy Framework,” 2011 International Conference on Communication Systems and Network Technologies, Katra, India, 2011, pp. 655-659, doi: 10.1109/CSNT.2011.141.
- Kumar, Sunil S., Shyam S. Karanth, K. C. Akshay, Ananth Prabhu, and Bharathraj M. Kumar. “Improved aprori algorithm based on bottom up approach using probability and matrix.” International Journal of Computer Science Issues (IJCSI) 9, no. 2 (2012): 242.
- Kumar, Sunil S., Santhosha Rao, and Shivaray Pai. “Moving Object Detection using Frame Interleaving and Clustering based Compression.” International Journal of Computer Technology and Applications 3, no. 4 (2012): 1583-1586.
Funded Projects
Title : Technology Aided Agriculture Optimization
Funding Agency : VGST
Funding Amount : 40 Lakh
Role : Co-Investigator
Dr. Sunil Kumar S.
Associate Professor and HOD
Dr.Prashanth C M
Educational Qualification:
- Ph.D. – Computer Engineering (National Institute of Technology Karnataka, Surathkal)
- M.E. – Computer Science & Engineering (Vellore Institute of Technology, Institute of Eminence, Vellore, Tamil Nadu)
- B.E. – Electronics & Communication Engineering (Kuvempu University, Karnataka)
Professional Experience:
He has 29 years of teaching and research experience in the domain of Computer Science & Engineering, which include more than two decades of administration as well in various capacities Technical Support Engineer, HOD, Chief Warden – Hostels, Researcher at IBM-CAS, Dean – Faculty Development and Principal. His areas of academic and research interest include Software Engineering, Social Computing, Operating Systems, and Parallel Computing.
He has guided one Ph.D. scholar and is currently guiding three. He has published more than 23 research articles in reputed journals and conferences. He has also evaluated several Ph.D. theses submitted to leading universities, including Pondicherry University, Vellore Institute of Technology, and the University of Madras.
Ph.D. Guided:
Mr. Vinai Biju George, – “Predictive Modelling for non-linear data in bioinformatics” – Visvesvaraya Technological University – Visvesvaraya Technological University, December 2021
Professional Body Memberships:
- Institute of Electrical and Electronics Engineers (IEEE)
- Indian Society for Technical Education (LMISTE) – LM26785
- System Society of India (LMSSI)
- International Association of Engineers (IEANG) – LM 118762
- Member Computer Society of India (CSI) – N1180478
University Assignments (Visvesvaraya Technological University, Belagavi):
- Academic Council Member – University Nominee: Canara College of Engineering, Mangalore, Karnataka (2025 – 2028).
- Academic Council Member – University Nominee: Maharaja Institute of Technology, Mysore (2024 – 2027).
- Deputy Chief Superintendent Examinations – JSSATE, Mauritius, December 2013.
- Board of Examiners (BoE), Member, Computer Science & Engineering, 2011 – 2012.
Dr.Prashanth C M
Principal & Professor
Ms. Radha E G
Educational qualification
B.E – Computer Science & Engg
M.Tech – Computer Science & Engg
Total Experience: 3.5 years
Area of Interest: Image processing, Machine Learning
Subject Handled · Data Structures and Applications · Discrete Mathematical Structures · Data Communication · Computer programming · Database management system· Computer Organization and Architecture· Digital Image Processing· Design and Analysis of Algorithms· Social Connect and Responsibility
Workshops/FDP/SDP Attended:
- Five Days Online Faculty Development Programme on “RPADD” Organized by UI path academic alliance, MITE, Mangalore [27th September to 1st October 2021].
- One week AICTE-VTU joint teacher traninng program on “An Overview of Teaching Techniques in Innovation & Design Thinking” Organized by VTU-HRDC, Centre for PG Studies, VIAT, Muddenahalli, Chikkaballapur[27th to 31st December 2021].
- Ten days online Faculty Development Programme on “Blockchain Technology-Applications,Issues and Challenges” organized by E&ICT Academy,NIT Waragangal and Mangalore Institute of Technolgy & Engineering,Mangalore during 21st February-2nd March,2022.
- Ten days online Faculty Development Programme on”AI/ML for computer vision and medical image analysis applications” organized by E&ICT Academy,NIT Waragangal and REVA university,Bengalur during 18th-27th April,2022.
- Five days online Faculty Develeopment Programme on “Introduction to Python and Its applications” Organized by VTU,Centre for PG Studies, VIAT, Muddenahalli, Chikkaballapur[13th to 17th March 2023].
- Five days online Faculty Develeopment Programme on “Robotics & Artificial Intelligence” Organized by VTU,Centre for PG Studies, VIAT, Muddenahalli, Chikkaballapur[24th to 28th March 2023].
Conference/Journal Publications
- Radha E G “Design and Implementation of Image dehazing using Histogram Equalization” in 3rd International Conference on Mobile Radio Communications & 5G Networks (MRCN 2022) on Feb 15,2023 [Springer Nature]
Ms. Radha E G
Assistant Professor
Ms. Shruthi K
Assistant Professor
Raghavendra Sooda
Education Qualifications:
- BE in Electronics and Communication from VTU,
- M.Tech in Power Electronics Control Systems from MIT Manipal,
- Pursuing Ph.D. in School of computer Engineering MIT Bengaluru, MAHE Manipal.
Subjects Handled:
- Cloud Computing,
- Artificial intelligence and Machine Learning,
- Embedded System, Computer Organization,
- Digital logic and embedded System,
- Embedded system and Arm processor,
- Microcontroller,
- Microprocessor,
- Sensor system and IOT,
- Signals and System.
Workshops/FDP Attended:
- Participated 2 Days Work Shop on Teaching Learning Process held during 17/5/24-18/5/24 in Sahyadri College of Engineering and Management Mangalore
- Participated 5 Days Work Shop on Research trends and opportunities in artificial intelligence and data science held during 27/3/23-31/3/23 in Sahyadri College of Engineering and Management Mangalore.
- Coordinated five days Faculty development program on Scilab in Canara Engineering College during January 2018.
- Attended 3 Days workshop on STM 32 introduction workshop in Canara Engineering College during January 2018.
- Conducted workshop to introduce Linux for students in Canara Engineering College during 2016.
- Attended the seminar MATLAB & Simulink for Engineering Education (March 2011) organized by MIT 2011.
- Attended one day symposium on recent advances in photonics (March 29th 2011) organized by centre for atomic and molecular physics Manipal university, Manipal
Conference/Journal Publications:
- Presented paper titled Machine Translation from Tulu to English using Transformer Architecture to IEEE AIDE- 2026 conference organized by NMAMIT Nitte.
- Accepted paper titled Voice Based Banking for Rural Areas to 3rd international conference on Emerging trends in Engineering and Medical Sciences -2026 conference organized by Yeshwant Rao Chavan College of Engineering, Nagpur.
- Presented Paper titled Speech to Speech Translation for Unwritten Language in 2nd international Conference on Computing machine Learning-2025 organized by Sikkim Manipal University, India.
- Writing research paper on Direct Speech to Speech translation for Indian Languages.
Raghavendra Sooda
Assistant Professor
Manjunath Prasad H. R
Education Qualifications –
- Bachelor of Engineering in Computer Science and Engineering, VTU, Belagavi |
- Master of Technology in Computer Network Engineering, VTU, Belagavi |
- Master of Science in Computer and Information Sciences, University of Massachusetts, USA |
- (Ph.D), VTU, Belagavi
Total Experience–
- 9 Years of teaching experience in India
- 5 Years of Software Application Development Industry experience across India and USA
Area of Interest–
- Vision Language Models,
- Computer Vision and
- Natural Language Processing
Subjects Handled–
- Cloud (Azure and AWS),
- Computer Vision and
- Natural Language Processing
Workshops/FDP Attended–
- Wipro certified Faculty – Salesforce Admin and Platform Developer – I
Technical Skills–
- Machine Learning Development – Python, PyTorch, NumPy, Pandas, SciPy, Scikit-Learn, Matplotlib, Seaborn, MATLAB (Deep Learning Toolbox)
- Backend Web Development – C# 14, ASP.NET 4.x, ASP.NET Core 10.0, MVC, Web API, Entity Framework, Razor Pages
- Frontend Web Development – ReactTS, Typescript 6.0, JavaScript, CSS3, HTML5
- Other Web Development Tools – Linq, JQuery, AJAX, Bootstrap 4
- Test Automation – Selenium and Microsoft Playwright
- Cloud – Microsoft Azure and Pivotal Cloud Foundry
- Database Technology – Microsoft SQL Server, MongoDB and Oracle
- Unit Testing – xUnit.net, NUnit, MS Test, Moq, Auto Fixture, Auto Moq and Fluent Assertions
- Continuous Integration / Continuous Delivery – Microsoft Azure DevOps and Atlassian Bamboo
- Version Control System – Git, Microsoft Azure DevOps and Atlassian Bit bucket
- Development Methodology – Agile and Waterfall
- Documentation – Atlassian Confluence, LATEX and Microsoft Word
- Microsoft Certified Developer and Devops Professional Expert
Manjunath Prasad H. R
Assistant Professor
Mr. MANJUNATH A NAIK
- M.Tech in CSE(VIT Vellore),
- BE in CSE(SDMIT Ujire)
- Machine Learning
- Deep Learning
- Machine Vision
- C programming
- Python Programming
- Django for Web Development.
- Got Best Paper Award in 3rd ICMREST Bengaluru 2025 for Presenting Paper Title “Crime Rate Prediction Application using Machine Learning Techniques”
- 3rd ICNAN-25, presented paper on “Explainable Morphology Clarification of Nanoparticles using Generative AI”
Mr. MANJUNATH A NAIK
Assistant Professor
Professor of Practice
Dr Chethan K
Professor of Practice
Mr Raghavendran V
Professor of Practice
Infrastructure
All the laboratories are well designed and equipped with latest computer systems. All systems are interconnected through LAN having sophisticated servers and internet connectivity with adequate bandwidth. All the laboratories have requisite software for undertaking all kinds of latest projects.
Major Labs
Algorithms Lab/ Artificial Intelligence Lab
The lab is equipped with 32 personal computers with latest configuration. PCs have windows 11 operating system with Java, Eclipse, Python and latest browsers. Students carry out programs related to Algorithms in Eclipse and Java and Artificial Intelligence practical in Python.
Data Structures/ DBMS lab
The lab is equipped with 32 personal computers with latest configuration. PCs are installed with Ubuntu operating system, C/C++, Java, MySQL and latest internet browser. Students perform practical related to solving data structure problems. Students perform database related practical and develop mini project in this lab.
Research Center
Department Forum – ARTIFERA
ARTIFERA – ARTIFICIAL INTELLIGENCE ERA is a student association of Artificial Intelligence & Machine learning department established on 17 th November, 2021. Its main objective is to create awareness and groom professionals skilled in the area of Artificial Intelligence & Machine learning. All students of Artificial Intelligence and Machine learning department are members of this association. It provides platform to the students to enhance their technical as well as non technical skills. ARTIFERA organizes various technical events like technical talks, workshops, quiz, project competition and exhibitions etc. In addition, department forum aims to promote research and entrepreneurial skills in students. Students are encouraged to participate in non technical events also for their holistic development.
“Our intelligence is what makes us human, and AI is an extension of that quality.” – Yann LeCun
Committee Members – Academic Year 2024-25
1. President: Mr. Amogha Acharya , 4th Year AIML
2. Vice President:
oMr. Abdul Rehman , 3rd Year AIML
oMs. Nandini Jagadish Hegde, 3rd Year CSE(AIML)
3. Secretary: Mr. Manoj N, 4th Year AIML
4. Joint Secretary: Ms. Nandini V C, 2nd Year AIML
5. Treasurer: Ms. Jenisha Shereyl Dsouza, 2nd Year CSE(AIML)
6. Sports Coordinator: Mr. Sujal Revankar, 3rd Year CSE(AIML)
7. Cultural Coordinator: Ms. Hitha B Mendon, 4th Year AIML
Activity Report
Academic Year 2024-25 Click Here
Academic Year 2023-24 Click Here
Academic Year 2022-23 Click Here
Academic Year 2021-22 Click Here
Study Materials
Syllabus
2023 – IV Year Scheme & Syllabus (Autonomous)- Click Here
2023 – III Year Scheme & Syllabus (Autonomous)- Click Here
2023 – II Year Scheme & Syllabus (Autonomous)- Click Here
2022 Scheme- Click Here
2021 Scheme- Click Here
2018 Scheme – Click Here
Model Question Paper (Autonomous)
Third Semester
| Engineering Mathematics- III | Click Here |
| Data Structures and Applications (23CSPC203) | Click Here |
| Digital System Design (23CSPC204) | Click Here |
| Computer Organization (23SCPC205) | Click Here |
| Software Engineering (23CSPC206) | Click Here |
| Universal Human Values (23HMCC215) | Click Here |
Fourth Semester
| Design and Analysis of Algorithms (23AIPC207) | Click Here |
| Introduction to Machine Learning(23AIPC208) | Click Here |
| Operating Systems (23AIPC209) | Click Here |
| Object Oriented Concepts with Java Programming (23AIPC210) | Click Here |
| Research Methodology & Intellectual Property Rights (23HMCC216) | Click Here |
Fifth Semester
| Entrepreneurship, Management & Finance (23HMCC301) | Click Here |
| Database Management Systems (23AIPC302) | Click Here |
| Computer Networks (23AIPC303) | Click Here |
| Mathematics for Artificial Intelligence (23AIPC304) | Click Here |
| Full Stack Development (23AIPE311) | Click Here |
Sixth Semester
| Artificial Intelligence (23AIPC306) | Click Here |
| Systems Engineering (23AIPC307) | Click Here |
| Business Intelligence (23AIPC308) | Click Here |
| Social Network Analysis (23AIPE322) | Click Here |
| Big Data Analytics (23AIPE323) | Click Here |
Study Materials
COURSE MATERIALS
AUTONOMOUS Scheme
OPEN ELECTIVE COURSE HAND BOOK FOR 6th SEM – 2026
| Course Code | Course Name | Couse Hand Book | Model Question Paper |
| 23AIOE322 | Introduction to Machine Learning | Click Here | Click Here |
6th Semester
| Artificial Intelligence [23AIPC306] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Systems Engineering [23AIPC307] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Business Intelligence [23AIPC308] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Social Network Analysis [23AIPE322] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Big Data Analytics [ 23AIPE322] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
5th Semester
| Entrepreneurship, Management Finance [23HMCC301] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Database management system [23AIPC302] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Computer Networks [23AIPC303] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Mathematics for Artificial Intelligence [23AIPC304] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Full stack development [23AIPE311] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
4th Semester
| Subject Code | Subject Name | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| 23AIPC207 | Design and Analysis of Algorithms | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| 23AIPC208 | Introduction to Machine Learning | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| 23AIPC209 | Operating Systems | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| 23HMCC216 | Research Methodology & Intellectual Property Right | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
VTU 22 Scheme
7th Semester
| Deep Learning & Reinforcement Learning [BAI701] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Machine Learning -II [BAI702] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Data Security & Privacy [BAD703] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| Data Engineering & MLOps [BAD714C] | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
6th Semester
| Subject Code | Subject Name | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| BAI601 | Natural Language Processing | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| BAI602 | Machine Learning -I | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| BIS613D | Cloud Computing and Security | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |
| BIKS609 | Indian Knowledge System | Module 1 | Module 2 | Module 3 | Module 4 | Module 5 |