Artificial Intelligence & Machine Learning


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


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.


  • 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

  • Puneet Mittal, Associate Professor & HoD, Chairperson
  • M S Ganesha Prasad, Principal, Member
  • Shreekumar, Associate Professor, CSE
  • Rajesh Kamath, Assistant Professor, ISE
  • Radha E G, Assistant Professor, Member
  • Shruthi Kotekar, Adjunct Faculty & Industry Expert, Member
  • Narendra VG, Associate Professor Department of Computer Science & Engineering, MIT, Manipal, Academic Expert
  • Kavyashree Kotekar, Glowtouch Technologies, Mangalore, Industry Expert
  • Prarthana Bhat, CSE-2011, Sr. Data Scientist, GSK, Alumni Representative



Mr. Sunil Kumar S.

Position: Senior Assistant Professor
Phone: #

Educational qualification

BE – Computer Science and Engineering

M.Tech – Software Engineering

Pursuing  Ph.D in Computer Science and Engineering (Wireless Sensor Networks)

Total experience

10 Years 6 Months

Area of Interest

  • IoT
  • Data Analytics

Professional Memberships


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


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.
  • 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),, 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

Mr. Sunil Kumar S.

Senior Assistant Professor

Ms. Radha E G

Position: Assistant Professor
Phone: #

Educational qualification

B.E – Computer Science & Engg

M.Tech – Computer Science & Engg

Areas of interest

  • Digital Image Processing
  • Computer Networks

Workshops /FDPs Attended


Conference/journal publications

  • Radha E.G Image and Video De-Hazing Algorithm Using Color Attenuation Priorin 7th  International Conference on Emerging Trends in Engineering (ICETE-2017) at NMAMIT, on 12th  May 2017, ISSN 2249-0426

Ms. Radha E G

Assistant Professor

Ms. Shruthi K

Position: Assistant Professor
Phone: #
Email: #

Educational Qualification

B.E, M.Tech

Total Experience

03 Years( Industry)



Ms. Shruthi K

Assistant Professor

Mr. Santosh Prabhakar

Position: Senior Assistant Professor
Phone: #
Email: #

Educational Qualification

  • B.E – Computer Science & Engineering
  • M.Tech – Computer Science & Engineering

Total Experience

11 Years

Professional Membership

  • Life time member of ISTE
  • International Association of Computer Science And Information Technology (IACSIT)
  • International Association Engineers(IAENG)

Area of Interest

  • Artificial Intelligence
  • Cryptography & Network Security

Subject Handled

  •  Computer Organization & Architecture
  • Cryptography
  • Design & Analysis Of Algorithm
  • Data Structure & Algorithm
  • Artificial Intelligence
  • Computer Networks.
  • Compiler Design.

Conference  &  Journal Papers

  • P.K.Adhvaryyu, Santosh Prabhakar International Conference on Application of Bio-inspired Social Spider Algorithm in Valve-point and Prohibited Operating Zones Constrained Optimal Load Flow of Combined Heat and Power System. At SIT West Bengal.(Springer)
  • Santosh Prabhakar, Harshvardhan Mathur, Security Enhancement in Deffie Hellman Algorithm at technology Research in Engineering Vol-1,Issue 8,April-2014. ISSN (Online): 2347 – 4718.

Mr. Santosh Prabhakar

Senior Assistant Professor

Dr.Prashanth C M

Position: Principal & Professor

Dr.Prashanth C M

Principal & Professor


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 2021-22
1. Mr. Prajeet Chendekar President, Second year
2. Mr. Karthik Raj Shetty Secretary, Second year
3. Mr. Dhruva Kumar Shetty Treasurer, Second year
4. Mr. Shreevatsan Placement Coordinator, Second year
5. Mr. Vishal Cultural Coordinator, Second year
6. Mr. Nandu Krishna G Sports Coordinator, Second year


Activity Report

Academic Year 2021-22 Click Here

Study Materials


2018 Scheme – Click Here

2021 Scheme- Click Here

Beyond Syllabus

News Letter