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

Computer Applications

Itm Sls Baroda University Vadodara
Duration
4 Years
Computer Applications UG OFFLINE

Duration

4 Years

Computer Applications

Itm Sls Baroda University Vadodara
Duration
Apply

Fees

₹2,50,000

Placement

93.5%

Avg Package

₹6,00,000

Highest Package

₹12,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Computer Applications
UG
OFFLINE

Fees

₹2,50,000

Placement

93.5%

Avg Package

₹6,00,000

Highest Package

₹12,00,000

Seats

120

Students

1,200

ApplyCollege

Seats

120

Students

1,200

Curriculum

Curriculum Overview

The Computer Applications program at Itm Sls Baroda University Vadodara is structured to provide a comprehensive educational experience over eight semesters. The curriculum balances theoretical knowledge with practical application, ensuring students are well-prepared for professional roles in the technology industry.

SemesterCourse CodeCourse TitleCredit (L-T-P-C)Prerequisites
ICS101Introduction to Programming3-0-0-3-
ICS102Mathematics for Computing4-0-0-4-
ICS103Digital Logic Design3-0-0-3-
ICS104English for Technical Communication2-0-0-2-
ICS105Introduction to Computer Science3-0-0-3-
ICS106Physics for Computing3-0-0-3-
ICS107Chemistry for Engineers3-0-0-3-
ICS108Workshop in Computer Applications0-0-2-1-
IICS201Data Structures and Algorithms4-0-0-4CS101
IICS202Object-Oriented Programming3-0-0-3CS101
IICS203Database Management Systems3-0-0-3CS101
IICS204Operating Systems3-0-0-3CS101
IICS205Discrete Mathematics3-0-0-3CS102
IICS206Computer Organization3-0-0-3CS103
IICS207Lab: Programming Lab0-0-2-1-
IIICS301Computer Networks3-0-0-3CS204
IIICS302Compiler Design3-0-0-3CS201
IIICS303Software Engineering3-0-0-3CS202
IIICS304Artificial Intelligence3-0-0-3CS201
IIICS305Human Computer Interaction3-0-0-3CS202
IIICS306Statistics for Computing3-0-0-3CS102
IIICS307Lab: Software Engineering Lab0-0-2-1-
IVCS401Machine Learning3-0-0-3CS304
IVCS402Cryptography and Network Security3-0-0-3CS301
IVCS403Data Mining3-0-0-3CS306
IVCS404Cloud Computing3-0-0-3CS301
IVCS405Mobile Application Development3-0-0-3CS202
IVCS406Web Technologies3-0-0-3CS202
IVCS407Lab: Machine Learning Lab0-0-2-1-
VCS501Advanced Database Systems3-0-0-3CS303
VCS502Distributed Systems3-0-0-3CS301
VCS503Big Data Analytics3-0-0-3CS403
VCS504Computer Vision3-0-0-3CS401
VCS505Internet of Things (IoT)3-0-0-3CS301
VCS506Game Development3-0-0-3CS202
VCS507Lab: IoT Lab0-0-2-1-
VICS601Reinforcement Learning3-0-0-3CS401
VICS602Neural Networks3-0-0-3CS401
VICS603Blockchain Technology3-0-0-3CS202
VICS604Network Security3-0-0-3CS402
VICS605Mobile Security3-0-0-3CS405
VICS606Web Application Security3-0-0-3CS406
VICS607Lab: Blockchain Lab0-0-2-1-
VIICS701Advanced Topics in AI3-0-0-3CS401
VIICS702Research Methodology3-0-0-3-
VIICS703Capstone Project0-0-4-4-
VIIICS801Internship0-0-0-6-
VIIICS802Final Year Thesis0-0-4-4-

Detailed Course Descriptions

The department offers a variety of advanced departmental elective courses that allow students to tailor their education according to their interests and career goals.

  • Machine Learning: This course delves into supervised and unsupervised learning techniques, neural networks, deep learning architectures, reinforcement learning, and practical applications in various domains. Students gain hands-on experience with libraries like TensorFlow, Keras, and Scikit-learn.
  • Cryptography and Network Security: Students explore symmetric and asymmetric encryption methods, digital signatures, hash functions, secure protocols, and network security vulnerabilities. Practical sessions include penetration testing using tools like Wireshark and Metasploit.
  • Data Mining: Focuses on extracting knowledge from large datasets through clustering, classification, association rule mining, and anomaly detection algorithms. Tools like Weka and Python-based libraries are extensively used.
  • Cloud Computing: Covers cloud service models (IaaS, PaaS, SaaS), virtualization technologies, containerization using Docker, orchestration with Kubernetes, and cloud architecture design principles. Hands-on labs include deploying applications on AWS and Azure platforms.
  • Mobile Application Development: Students learn to develop cross-platform apps using Flutter and React Native frameworks, integrating with REST APIs, handling local storage, and implementing secure authentication mechanisms.
  • Web Technologies: Explores modern web development practices including responsive design, JavaScript frameworks (React, Angular), Node.js backend development, and database integration with MongoDB and PostgreSQL.
  • Human Computer Interaction: Studies cognitive psychology, usability testing, interaction design principles, prototyping tools, and user experience evaluation methods. Students create interactive prototypes using Figma and Adobe XD.
  • Internet of Things (IoT): Introduces sensor networks, embedded systems programming, wireless communication protocols, edge computing, and smart city applications. Labs involve building IoT projects using Raspberry Pi and Arduino microcontrollers.
  • Game Development: Covers game design principles, graphics rendering engines, physics simulation, scripting languages (C#), and mobile game development using Unity engine. Students build complete games from concept to release.
  • Blockchain Technology: Explores blockchain architecture, smart contracts, consensus algorithms, decentralized applications (dApps), and cryptocurrency systems. Practical sessions include building Ethereum-based dApps with Solidity and Truffle frameworks.

Project-Based Learning Framework

The department emphasizes project-based learning as a core component of the curriculum. Students engage in mandatory mini-projects during their second and third years, followed by a comprehensive final-year thesis or capstone project.

Mini-projects are designed to reinforce classroom concepts through practical implementation. Each group consists of 3-4 students who select projects based on their interests and faculty guidance. Projects may be industry-sponsored, research-oriented, or community-focused. Evaluation criteria include technical proficiency, creativity, teamwork, documentation quality, and presentation effectiveness.

The final-year thesis/capstone project spans two semesters and involves significant independent research. Students work closely with faculty mentors to define research questions, design experiments, gather data, analyze results, and present findings at departmental symposiums. This process develops critical thinking, problem-solving, and academic writing skills essential for post-graduate studies or industry roles.