DEPARTMENT OF Artificial Intelligence and machine learning

The field of Computer Science and Engineering, specifically in the areas of Artificial Intelligence/Data Science, is experiencing exponential growth and focuses on utilizing various tools and techniques to extract valuable insights from data. The program is designed as an interdisciplinary, problem-solving-oriented subject that leverages scientific methods to address practical challenges, and covers topics such as artificial intelligence and machine learning. The course curriculum incorporates a combination of data inference, algorithm development, and cutting-edge technology to effectively analyze and solve complex problems.

About the Course

The Artificial Intelligence and Machine Learning course is an interdisciplinary field that is aimed at solving practical problems using scientific techniques. The course is designed to teach students how to use tools and techniques to extract useful information from data. The course curriculum includes a combination of data inference, algorithm development, and technology, which is used to analyze and solve complex problems. Students will learn about topics such as artificial intelligence, machine learning, and data science, which will enable them to develop intelligent systems that can learn from data and make predictions or decisions based on that data. The course also covers topics such as deep learning, neural networks, and natural language processing, which are used to build intelligent systems that can perform tasks such as speech recognition, image recognition, language translation, etc. Overall, the Artificial Intelligence and Machine Learning course is a highly valuable and in-demand field that prepares students to become experts in data analysis and intelligent systems development.

Course Duration: 4 years (Regular)    |    3 years (Lateral Entry)
No. of Semesters: 8 (Regular)    |    6 (Lateral Entry)
No. of Seats: 120
Eligibility: 10+2 System of Education. Must have secured a pass in Physics, Chemistry and Mathematics in the qualifying examination with 45% marks in aggregate.
Scope for Higher Studies: M.E.    |    M. Tech    |    M.B.A.   |    M.S.

Program Highlights:

  • Integrated Liberal education program to gain insights into subjects like Psychology,Design Thinking, Critical Thinking
  • Student-centered pedagogy
  • Curriculum focused on recent trends
  • Blended & Hybrid Learning
  • Provides opportunities for hands-on and experiential learning
  • Promoting deep learning through project-based learning
  • Preparing students for evolving job roles in the chosen area of specialization
  • Emphasis on design-oriented thinking, Communication, Collaboration and Creativity
  • Offers flexibility in choosing elective courses for the understanding of emerging technologies
  • Offers major, minor and specialization as part of the four-year programme
  • Startup ecosystem to translate the idea into business models
  • Encourage Entrepreneurship
  • Targeted towards equipping students for future skill sets

Career Opportunities

Artificial intelligence, machine learning, and data science are fields that are currently experiencing rapid growth, with the potential to shape the future of various industries. These fields involve the development and application of advanced algorithms and computational models to analyze and extract insights from large datasets. Artificial intelligence, in particular, involves the creation of intelligent machines that can perform tasks typically requiring human intelligence, such as recognizing speech, making decisions, and understanding natural language. Machine learning, on the other hand, is a subset of artificial intelligence that focuses on the development of algorithms that enable machines to learn from data and improve their performance over time. Data science is an interdisciplinary field that combines statistics, computer science, and domain-specific knowledge to extract insights and knowledge from data. Data scientists use various techniques such as data mining, machine learning, and statistical analysis to identify patterns and make predictions. These fields are increasingly being applied in diverse industries, including healthcare, finance, manufacturing, and technology. For instance, in healthcare, artificial intelligence and machine learning are being used to improve disease diagnosis and develop personalized treatments. In finance, these fields are used to analyze financial data and detect fraud. In manufacturing, they are used to optimize supply chain management and improve product quality.

Department Best Practices

  • Implementation of Mentor-Mentee concept: Enables focus on individual students, increasing the scope of giving guidance, counselling and monitoring for better improvement of every student.
  • Enhancement of Programming Language skills: The department organizes various workshops on emerging technologies amongst students for better career prospects and the development of technical skills in the students.
  • Peer to Peer Learning: The students participate in mock interviews and group discussions to give them a sense of confidence and groom them towards professionalism.
  • Activity-based Learning: The best teaching practice-formative assessment, and assignment design to foster student engagement and ownership.
  • Placement Oriented Training: Campus recruitment training is given to the students from II year onwards to cater for the needs of students for placements.
  • Organizing Workshops and Guest Lectures:Reputed persons from the software industry and academicians are invited to the campus to give expert talks on emerging technologies.
  • Faculty Development Programmes (FDPs): The department organizes FDPs and also deputes the faculty members to other organizations to enhance their knowledge with advanced technologies.
  • Research-Oriented Promotions: Research and Development (R&D) cell play a critical role in the process of innovation.
  • Incubation Cell: With the support of the Incubation cell, our students will be encouraged to do Live Projects offered by college or industry.
  • Internships: Internship is a system of on-the-job training provided for our students in a real-time environment of the IT Industry. Internships provide opportunities for students to gain experience in their field and determine if they have an interest in a particular career.
  • Centre of Excellence in Artificial Intelligence and Machine Learning: Creating an Artificial Intelligence Center of Excellence for fostering groundbreaking research to develop the solutions that addresses societal problems. Grant sanctioned-Rs. 30.00 Lakhs under Karnataka fund for infrastructure strengthening in science and technology (KFIST-L ll).


CSE (Artificial intelligence and machine learning) Organized workshop on data science field

Awareness Programs Dept of CSE ( Artificial intelligence and machine learning ) organized technical talk on ‘how to crack job in data science field’. It was a motivational session by a successful innovator in the field of data science -Mr Shanthanu Shubham, SDE, Amazon. He briefed the students on data science, its scope and application. He threw light on concepts related to machine learning and its future.

CSE (Artificial intelligence and machine learning) Organized workshop on Student Entrepreneurship

Awareness Programs Dept. of CSE (Artificial Intelligence and Machine Learning), for the occasion of National Youth Day Celebration organized a Talk on Student Entrepreneurship on 12th January 2023 in association with SIGMA - Student's association. The resource person was Shobith Mallya, a student of ISE Dept., SCEM and Co-founder of Effinity. He motivated the students how starting Entrepreneurships at university level allows a student to gain the necessary life skills and confidence to get into the real world.


# Name Qualification Designation Specialization Profile
1 Mr Sharathchandra N R M.Tech Assistant Professor Microelectronics and Control System Link
2 Chaithanya Lakshmi M M.Tech Assistant Professor Information technology Link
3 Vaishnavi V Rao M.Tech Assistant Professor Cyber Security Link
4 Manjunatha E C M.Tech Assistant Professor Computer science and engineering Link
5 Nebeesath Sunaina M.Tech Assistant Professor Computer science and engineering Link
6 Mr. Shobhan Kumar M.Tech Assistant Professor Machine Learning Link
7 Sweekrithi M Shetty M.Tech Assistant Professor Machine Learning Link
8 Mrs Deepthi L M.Tech Assistant Professor Computer Network Engineering Link
9 Mrs Majina K M.Tech Assistant Professor Comuter Science and Engineering Link
10 Ms Sandra Jeyes M.Tech Assistant Professor Computer and Information Science Link
11 MR. Ganaraj K M.Tech Assistant Professor Computer Science & Engineering Link
12 MR. Gurusiddayya Hiremath M.Tech Assistant Professor Bio-Medical Image Processing, Machine Learning, Deep Learning Link

Adjunct Faculty

# Name Qualification Designation in External
1 Dr Raghavendra S Ph D Associate professor
2 Dr Diwakaruni Syam Sundar Ph D Professor