Collegese

Welcome to Collegese! Sign in →

Collegese
  • Colleges
  • Courses
  • Exams
  • Scholarships
  • Blog

Search colleges and courses

Search and navigate to colleges and courses

Start your journey

Ready to find your dream college?

Join thousands of students making smarter education decisions.

Watch How It WorksGet Started

Discover

Browse & filter colleges

Compare

Side-by-side analysis

Explore

Detailed course info

Collegese

India's education marketplace helping students discover the right colleges, compare courses, and build careers they deserve.

© 2026 Collegese. All rights reserved. A product of Nxthub Consulting Pvt. Ltd.

Apply

Scholarships & exams

support@collegese.com
+91 88943 57155
Pune, Maharashtra, India

Duration

4 Years

Bachelor of Technology in Engineering

Itm Sls Baroda University Vadodara
Duration
4 Years
Engineering UG OFFLINE

Duration

4 Years

Bachelor of Technology in Engineering

Itm Sls Baroda University Vadodara
Duration
Apply

Fees

₹2,50,000

Placement

92.0%

Avg Package

₹5,20,000

Highest Package

₹8,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Engineering
UG
OFFLINE

Fees

₹2,50,000

Placement

92.0%

Avg Package

₹5,20,000

Highest Package

₹8,00,000

Seats

300

Students

1,200

ApplyCollege

Seats

300

Students

1,200

Curriculum

Curriculum Overview

The engineering program at Itm Sls Baroda University Vadodara is structured over eight semesters, with a progressive curriculum designed to build both foundational knowledge and specialized expertise. Each semester includes core courses, departmental electives, science electives, and laboratory components that collectively foster an immersive learning experience.

SemesterCourse CodeFull Course TitleCredit Structure (L-T-P-C)Prerequisites
1ENG101Engineering Mathematics I3-1-0-4-
1ENG102Physics for Engineers3-1-0-4-
1ENG103Chemistry for Engineers3-1-0-4-
1ENG104Engineering Drawing & Computer Graphics2-1-0-3-
1ENG105Communication Skills2-0-0-2-
1ENG106Programming for Engineers3-1-0-4-
1ENG107Basic Electrical Engineering3-1-0-4-
2ENG201Engineering Mathematics II3-1-0-4ENG101
2ENG202Materials Science & Metallurgy3-1-0-4-
2ENG203Thermodynamics3-1-0-4-
2ENG204Fluid Mechanics & Hydraulic Machines3-1-0-4-
2ENG205Strength of Materials3-1-0-4-
2ENG206Computer Programming & Data Structures3-1-0-4ENG106
2ENG207Electronic Devices & Circuits3-1-0-4-
3ENG301Engineering Mathematics III3-1-0-4ENG201
3ENG302Design & Analysis of Algorithms3-1-0-4ENG206
3ENG303Digital Logic Design3-1-0-4-
3ENG304Signals & Systems3-1-0-4-
3ENG305Control Systems3-1-0-4-
3ENG306Electromagnetic Fields & Waves3-1-0-4-
3ENG307Manufacturing Processes3-1-0-4-
4ENG401Probability & Statistics3-1-0-4ENG201
4ENG402Database Management Systems3-1-0-4ENG206
4ENG403Computer Networks3-1-0-4-
4ENG404Operating Systems3-1-0-4-
4ENG405Microprocessors & Microcontrollers3-1-0-4-
4ENG406Machine Learning Fundamentals3-1-0-4-
4ENG407Power Electronics & Drives3-1-0-4-
5ENG501Advanced Mathematics for Engineers3-1-0-4ENG201
5ENG502Software Engineering & Project Management3-1-0-4-
5ENG503Data Mining & Warehousing3-1-0-4-
5ENG504Embedded Systems Design3-1-0-4-
5ENG505Renewable Energy Systems3-1-0-4-
5ENG506Robotics & Automation3-1-0-4-
5ENG507Hydraulic & Pneumatic Systems3-1-0-4-
6ENG601Advanced Algorithms3-1-0-4ENG302
6ENG602Computer Vision & Image Processing3-1-0-4-
6ENG603Cybersecurity Principles3-1-0-4-
6ENG604Artificial Intelligence3-1-0-4-
6ENG605Nanotechnology & Materials Science3-1-0-4-
6ENG606Industrial Design & Product Development3-1-0-4-
6ENG607Power System Protection3-1-0-4-
7ENG701Capstone Project I2-0-0-2-
7ENG702Advanced Topics in Engineering3-1-0-4-
7ENG703Research Methodology & Ethics3-1-0-4-
7ENG704Entrepreneurship & Innovation3-1-0-4-
7ENG705Advanced Control Systems3-1-0-4-
7ENG706Biomedical Instrumentation3-1-0-4-
7ENG707Environmental Engineering3-1-0-4-
8ENG801Capstone Project II2-0-0-2-
8ENG802Internship4-0-0-4-
8ENG803Professional Practice & Ethics3-1-0-4-
8ENG804Final Year Thesis2-0-0-2-
8ENG805Advanced Elective I3-1-0-4-
8ENG806Advanced Elective II3-1-0-4
8ENG807Advanced Elective III3-1-0-4

Advanced departmental elective courses are offered in the later semesters to allow students to specialize in areas of interest. These courses include:

  • Machine Learning Fundamentals: This course introduces students to supervised and unsupervised learning techniques, neural networks, deep learning frameworks, and practical applications in real-world scenarios.
  • Computer Vision & Image Processing: Students learn about image segmentation, object detection, facial recognition, and computer vision algorithms used in autonomous vehicles and medical imaging systems.
  • Cybersecurity Principles: The course covers encryption methods, network security protocols, ethical hacking, and incident response strategies to protect digital assets.
  • Artificial Intelligence: This course delves into AI concepts including robotics, natural language processing, and reinforcement learning with hands-on projects.
  • Nanotechnology & Materials Science: Students explore the behavior of matter at atomic and molecular scales, focusing on nanomaterials synthesis and applications in electronics and medicine.
  • Advanced Algorithms: The course focuses on designing and analyzing complex algorithms, including graph theory, dynamic programming, and approximation algorithms.
  • Robotics & Automation: Students study robot kinematics, control systems, sensor integration, and automation technologies used in manufacturing and logistics.
  • Embedded Systems Design: This course teaches students how to design and program embedded systems using microcontrollers, real-time operating systems, and hardware-software integration.
  • Data Mining & Warehousing: The course covers data preprocessing, clustering, classification, association rule mining, and data warehouse architecture for business intelligence.
  • Software Engineering & Project Management: Students learn about software development lifecycle, agile methodologies, risk management, and project planning tools.

The philosophy of project-based learning at Itm Sls Baroda University Vadodara emphasizes collaborative problem-solving, innovation, and real-world impact. Mini-projects are introduced in the third year, allowing students to apply theoretical knowledge to practical challenges. These projects are assessed based on innovation, technical execution, documentation quality, and team collaboration.

Final-year capstone projects are more comprehensive, requiring students to undertake independent research or develop a full-scale solution to a complex engineering problem. Students are paired with faculty mentors who guide them through the research process, methodology, experimentation, and presentation of findings. The evaluation criteria include originality, technical depth, feasibility, impact, and communication skills.

Students can select their projects based on personal interest, mentor availability, or industry collaboration opportunities. The university encourages interdisciplinary projects that integrate knowledge from multiple domains to address complex societal issues.