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Pune, Maharashtra, India

Duration

4 Years

Computer Applications

Uka Tarsadia University Surat
Duration
4 Years
Computer Applications UG OFFLINE

Duration

4 Years

Computer Applications

Uka Tarsadia University Surat
Duration
Apply

Fees

₹4,50,000

Placement

92.0%

Avg Package

₹6,00,000

Highest Package

₹12,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Computer Applications
UG
OFFLINE

Fees

₹4,50,000

Placement

92.0%

Avg Package

₹6,00,000

Highest Package

₹12,00,000

Seats

120

Students

300

ApplyCollege

Seats

120

Students

300

Curriculum

Comprehensive Course Structure and Curriculum

The Computer Applications program at Uka Tarsadia University Surat is structured over eight semesters, with a carefully designed curriculum that balances theoretical foundations with practical applications. The program is divided into core subjects, departmental electives, science electives, and laboratory sessions to provide students with a holistic educational experience.

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
1CS101Engineering Mathematics I3-1-0-4-
1CS102Engineering Physics3-1-0-4-
1CS103Basic Electrical Engineering3-1-0-4-
1CS104Introduction to Programming3-0-2-5-
1CS105Computer Organization3-1-0-4-
1CS106English for Communication3-0-0-3-
2CS201Engineering Mathematics II3-1-0-4CS101
2CS202Material Science3-1-0-4-
2CS203Electronics Devices3-1-0-4-
2CS204Data Structures and Algorithms3-1-2-6CS104
2CS205Object Oriented Programming3-1-2-6CS104
2CS206Environmental Science3-0-0-3-
3CS301Engineering Mathematics III3-1-0-4CS201
3CS302Database Management Systems3-1-2-6CS204
3CS303Operating Systems3-1-2-6CS205
3CS304Computer Networks3-1-2-6CS205
3CS305Software Engineering3-1-2-6CS205
3CS306Discrete Mathematics3-1-0-4CS201
4CS401Engineering Mathematics IV3-1-0-4CS301
4CS402Compiler Design3-1-2-6CS303
4CS403Web Technologies3-1-2-6CS305
4CS404Mobile Application Development3-1-2-6CS305
4CS405Artificial Intelligence3-1-2-6CS302
4CS406Human Computer Interaction3-1-2-6CS305
5CS501Machine Learning3-1-2-6CS405
5CS502Cybersecurity3-1-2-6CS304
5CS503Cloud Computing3-1-2-6CS303
5CS504Data Mining3-1-2-6CS302
5CS505Embedded Systems3-1-2-6CS205
5CS506Project Management3-0-0-3-
6CS601Big Data Technologies3-1-2-6CS504
6CS602Internet of Things3-1-2-6CS505
6CS603Software Testing3-1-2-6CS305
6CS604Game Development3-1-2-6CS404
6CS605Advanced Database Systems3-1-2-6CS302
6CS606Research Methodology3-0-0-3-
7CS701Capstone Project I0-0-6-6CS606
7CS702Advanced Topics in AI3-1-2-6CS501
7CS703Advanced Cybersecurity3-1-2-6CS502
7CS704DevOps and Containerization3-1-2-6CS503
7CS705Specialized Elective I3-1-2-6-
7CS706Specialized Elective II3-1-2-6-
8CS801Capstone Project II0-0-6-6CS701
8CS802Internship0-0-0-12CS701
8CS803Professional Ethics3-0-0-3-
8CS804Entrepreneurship3-0-0-3-
8CS805Specialized Elective III3-1-2-6-
8CS806Specialized Elective IV3-1-2-6-

Advanced Departmental Elective Courses

Departmental electives are designed to provide students with in-depth knowledge in specialized areas of computer applications. These courses are offered in the latter semesters and are intended to allow students to explore advanced topics and prepare for specialized careers.

One such course is Machine Learning, which covers advanced topics in supervised and unsupervised learning, neural networks, deep learning frameworks, and reinforcement learning. This course is led by Dr. Priya Sharma and focuses on practical implementation using Python and TensorFlow. Students are expected to complete a project involving real-world datasets and develop a machine learning model that can be deployed in production environments.

Cybersecurity is another crucial elective that delves into network security, cryptography, ethical hacking, and incident response. This course is taught by Dr. Rajesh Patel, who brings extensive industry experience in developing secure systems. Students learn to identify vulnerabilities, implement security measures, and conduct penetration testing using industry-standard tools.

The Cloud Computing course introduces students to cloud architecture, virtualization, containerization, and DevOps practices. Led by Dr. Arjun Desai, this course provides hands-on experience with AWS, Microsoft Azure, and Google Cloud Platform. Students are required to design and deploy scalable cloud solutions for real-world applications.

Data Mining is a course that focuses on extracting useful information from large datasets. Students learn about data preprocessing, clustering, classification, association rules, and anomaly detection. This course is led by Dr. Sunita Reddy and includes projects that involve analyzing large-scale datasets to derive actionable insights.

Embedded Systems is a course that teaches the design and implementation of systems that are embedded in physical devices. Students learn about microcontrollers, real-time systems, sensor networks, and embedded software development. This course is led by Dr. Vipin Gupta and includes laboratory sessions where students build and test embedded systems.

Big Data Technologies covers the principles and practices of processing and analyzing large datasets using tools such as Hadoop, Spark, and Kafka. This course is led by Dr. Sunita Reddy and provides students with hands-on experience in building big data pipelines and implementing data analytics solutions.

Internet of Things introduces students to the design and implementation of IoT systems. Students learn about sensors, actuators, wireless communication protocols, and IoT platforms. This course is led by Dr. Vipin Gupta and includes projects that involve building smart home and industrial IoT solutions.

Software Testing focuses on the principles and practices of software testing, including test planning, test design, and test automation. This course is led by Dr. Anjali Mehta and includes practical sessions where students learn to use tools such as Selenium and JUnit for automated testing.

Game Development is a course that teaches the fundamentals of game design and development using game engines such as Unity and Unreal Engine. Students learn about game mechanics, level design, and user interface design. This course is led by Dr. Anjali Mehta and includes a final project where students develop a complete game.

Advanced Database Systems covers advanced topics in database design and implementation, including distributed databases, NoSQL systems, and database security. This course is led by Dr. Anjali Mehta and includes projects that involve designing and implementing complex database solutions.

Research Methodology is a course that introduces students to the principles and practices of research in computer applications. Students learn about literature review, hypothesis formulation, data collection, and research writing. This course is led by Dr. Rajesh Patel and prepares students for their capstone projects and thesis work.

Project-Based Learning Philosophy

Project-based learning is a core component of the Computer Applications program at Uka Tarsadia University Surat. This approach emphasizes hands-on experience, collaborative work, and real-world problem-solving. Students are encouraged to work on projects that address real-world challenges and contribute to the field of computer applications.

The program includes mandatory mini-projects in the third and fourth semesters, followed by a comprehensive final-year thesis or capstone project. These projects are designed to integrate the knowledge and skills acquired throughout the program and to provide students with the opportunity to demonstrate their expertise in a specific area of interest.

Mini-projects are typically completed in teams of 3-5 students and are supervised by faculty mentors. Students are required to submit progress reports, present their work, and demonstrate their solutions to a panel of experts. These projects are evaluated based on technical merit, innovation, and presentation quality.

The final-year capstone project is a significant undertaking that requires students to work on an independent research or development project under the guidance of a faculty mentor. Students are expected to conduct a literature review, design and implement a solution, and present their findings in a comprehensive report and oral presentation. This project is a culmination of the student's learning and serves as a portfolio piece that showcases their skills and expertise to potential employers.

Project selection is a collaborative process that involves faculty mentors and students. Students are encouraged to choose projects that align with their interests and career goals. The program also offers opportunities for students to collaborate with industry partners on real-world projects, providing them with valuable experience and exposure to industry practices.