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Curriculum

Pedagogy

Effective and Innovative pedagogy plays an important role in improving the quality of teaching-learning and ensures attainment of learning objectives. The Institute has well-defined policies and internal quality assurance system to achieve quality in teaching-learning process. At the Department level, a well-defined system is in place to design the content and monitor delivery of the same. ICT tools are used extensively to support, enhance, and optimise the teaching and learning experience. Lectures, tutorials and laboratory sessions form the essential components of pedagogy. Emphasis is also on project based learning in the form of minor and major projects, where students work on live problem definitions and research ideas. Industrial visits, a fraction of courses taught by industry experts and internships give students a flavor of the current practices and advancements in the industry.

Assessment

The evaluation process has mainly three components, Continuous Evaluation (CE), Laboratory and Practical Work (LPW), Project Work (PW) and Semester End Examination (SEE). The components may vary depending on the nature of the course. These components effectively lead to the attainment of course outcomes and hence the POs and PSOs.

Course Code Course Name
3EI105CC24 Industrial Instrumentation
3EI106CC24 Process Automation
4FT901CC24 Research Methodology and Seminar
3FT901CC24 Summer Internship

Department Elective – II with Laboratory

Course Code Course Name
3EI603ME24 Image Processing and its application
3EI107ME24 Factory Automation
3EI303ME24 Robotic Control System
Course Code Course Name
3EI107ME24 Factory Automation
Elective Course – I
Course Code Course Name
3EI604IE24 Edge computing application in Automation
3EI403IE24 Sensors and Transducers
3EI605IE24 Advanced Microcontrollers

 

Course Code Course Name
4EI601CC25 Embedded System Design
4FT901CC24 Research Methodology and Seminar
Department Elective – III
Department Elective – IV

Department Elective – III with Laboratory

Course Code Course Name
4EI501ME25 Deep Learning for Vision Systems
4EI101ME25 Nonlinear and Digital Control
4EI102ME25 Fuzzy Control Theory

Department Elective – IV without Laboratory

Course Code Course Name
4EI201ME25 Data Communication and Industrial Networking
4EI103ME25 Power Plant Automation
4EI401ME25 Soft Sensors
4EI602ME25 VLSI Design

Elective Course – II

Course Code Course Name
4FT902CC25 Research Project / Internship
Course Code Course Name
6EI851CC25 Research Methodology and IPR
6ME851CC25 Mobile Robot
6CS401CC25 Machine and Deep Learning
6CS851CC25 Digital Image Processing
Elective – I
Elective – II
6EI891CC25 Minor Project

Pool of Elective I

Pool of Elective II

Course Code Course Name
6ME871ME25 Aerial Robotics
6ME872ME25 Underwater Robotics
6ME873ME25 Soft Robotics
Course Code Course Name
6EIXXX Major Project Part – I (Full Time)
Course Code Course Name
6EIXXX Major Project Part – II (Full Time)