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.
Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is the science and engineering of making intelligent machines, especially intelligent computer programs. Knowledge Engineering is an essential part of AI research. Machines and programs need to have bountiful information related to the world to often act and react like human beings. AI initiates common sense, problem-solving and analytical reasoning power in machines, which is much difficult and a tedious job. AI and Machine Learning (ML) are the part of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems. ML is a subfield of artificial intelligence, which enables machines to learn from past data or experiences without being explicitly programmed.
The major focus of the programme is to equip the students who wish to acquire the ability to design intelligent solutions to real-time problems. This programme discusses artificial intelligence methods based on different fields like neural networks, signal processing and data mining, etc.
Program Overview:
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
- AI and Machine Learning Lab
- Web Applications Lab
- Mobile Application Development & Robotics Lab
- Internet of Things Lab
Career Opportunities
Graduates of the program will be well prepared to work across many sectors, including medicine, finance, robotics, and business intelligence Additionally, you will have a strong technical foundation to pursue graduate work in computer science or AI.
- Software developer
- Artificial intelligence engineer
- Data scientist
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
Department Advisory Board
- Mr. Sunil Kumar, Senior Assistant Professor & HoD, Chairperson
- Dr. Prashanth C M, Principal, Member
- 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
Dr. YOGEESHA C.B
Educational Qualification:
- B.E (Computer Science & Engineering)
- M.Tech (Computer Science & Engineering)
- PhD(Computer Science & Engineering)
Total Experience:
- 25 Years 3 Months
Area of Interest:
- Evolutionary Technologies
- Artificial Intelligence (AI)
- Advance Algorithms
- Software Engineering
- Virtualization.
Subjects Handled:
- Data Structures (Basic & Advance)
- Analysis and Design of Algorithms (ADA)
- Software Engineering
- System Software
- Artificial Intelligence
- Advanced Computer Architecture
- Microprocessor.
Professional Membership:
- Life Member of Indian Society of Technical Education (LMISTE) – LM33729
Conference/Journal Publications :
- “An Approach to Design and Implementation of Dynamic Geometric Travelling Salesperson Problem using Hopefield Neural Network Model”, in International Journal of Technology and Engineering System (IJTES) http://www.ijcns.com/pdf/ijtesvol6no1-10.pdf, ISSN:0976-1345, Vol6, No 1, Jan-March 2014, pp 58-64.
- “Highly Scalable Model for Tests Execution in Cloud Environments”, IEEE, 2012 18th International Conference on Advanced Computing and Communications (ADCOM), https://ieeexplore.ieee.org/abstract/document/6563584, 14-16 Dec. 2012
- “Mechanism for on demand Tag-Based software testing in virtualized environments”, IEEE 2012 Fourth International Conference on Advanced Computing (ICoAC), https://ieeexplore.ieee.org/abstract/document/6416808, 13-15 Dec. 2012
- “A Relative Study of Genetic Algorithms and Hopfield Neural Network to Optimize Shortest Path Routing Algorithms for Finding Drilling Holes on the Printed Circuit Board-PCB” Journal of Advanced Research in Dynamical and Control Systems – JARDCS, ISSN 1943-023X, Dec 2017, 15th Special Issue, http://www.jardcs.org/abstract.php?archiveid=2187, pp 801-808
- “Solution to Solve Travelling Spider Problem (TSpP) Using nXn Hopfield Network” Journal of Advanced Research in Dynamical and Control Systems – JARDCS, ISSN 1943-023X, Dec 2017, 15th Special Issue, http://www.jardcs.org/abstract.php?archiveid=2186, pp 793-800.
- Randomized Algorithms: On the Improvement of Searching Techniques Using Probabilistic Data Structure Linear Linked Skip Lists, Proceeding of ICAdC, AISC, springerlink, http://link.springer.com/chapter/10.1007/978-81-322-0740-5_19, pp 147-153, 2012
- Enhanced Relative Comparison of Traditional Sorting Approaches towards Optimization of New Hybrid Two-in-One (OHTO) Novel Sorting Technique, Journal of ICT Research and Applications, 17(2), 151-166. https://doi.org/10.5614/itbj.ict.res.appl.2023 .1 7.2.2, 2023
Dr. YOGEESHA C.B
Dean & Professor
Dr ARCHANA NANDIBEWOOR
Education Qualifications: MTech(CSE),PhD
Total Experience: 19+ years
Area of Interest: Remote sensing, Image Processing, Machine Learning
Subjects Handled: Data science, Cloud computing, Microcontrollers, Artificial Intelligence & Machine Learning, Compiler Design, Software engineering, Digital electronics etc
Workshops/FDP:
Organised: 05
Attended: 30
Sponsored Projects: Two Ongoing projects funded by AR&DB, DRDO, Ministry of Defense , New Delhi worth Rs.33.61 Lakhs and Unnath Bharath Abhiyaan,New Delhi worth Rs 1 Lakh
Conference/Journal Publications: 17+ papers
Patent:01
Book chapters: 01
Orcid Id: 0000-0002-3698-6057 Scopus ID: 55901791600
Dr ARCHANA NANDIBEWOOR
ASSOCIATE PROFESSOR
Dr. M.Amirthavalli
Educational Qualification: M.E (CS&E), Ph.D
Total Experience:7
Area of Interest: Cryptography and Network Security, Machine Learning, Secure Programming
Subjects Handled: Computer Networks, Python Programming, Unix and Network Programming, Secure Programming, Java.
Dr. M.Amirthavalli
Assistant Professor
Mr. Srivatsa Upadhya P
Education Qualification:
- BTech (CSE)
- MTech (SE)
Total Experience: 1year 3months
Area of Interest: Log Analysis, Data Obfuscation, Linux, Python, ELK Stack, Machine Learning.
Mr. Srivatsa Upadhya P
Assistant Professor
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.
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 2023-24 Click Here
Study Materials
Syllabus
2022 Scheme- Click Here
2023 Scheme & Syllabus (Autonomous) – 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 |