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+91 88943 57155
Pune, Maharashtra, India

Duration

4 Years

Bachelor of Technology in Computer Science

Shyam University Dausa
Duration
4 Years
Computer Science UG OFFLINE

Duration

4 Years

Bachelor of Technology in Computer Science

Shyam University Dausa
Duration
Apply

Fees

₹12,00,000

Placement

92.0%

Avg Package

₹4,50,000

Highest Package

₹8,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Computer Science
UG
OFFLINE

Fees

₹12,00,000

Placement

92.0%

Avg Package

₹4,50,000

Highest Package

₹8,00,000

Seats

150

Students

1,500

ApplyCollege

Seats

150

Students

1,500

Curriculum

Comprehensive Course Structure

The curriculum for the Bachelor of Technology in Computer Science at Shyam University Dausa is meticulously designed to provide a comprehensive and progressive learning experience over four years. The program is divided into eight semesters, with each semester comprising a combination of core courses, departmental electives, science electives, and laboratory sessions. The following table outlines the course structure for each semester:

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
1CS101Introduction to Programming3-0-0-3None
1CS102Mathematics for Computer Science3-0-0-3None
1CS103Physics for Computer Science3-0-0-3None
1CS104English for Communication3-0-0-3None
1CS105Computer Organization and Architecture3-0-0-3None
1CS106Lab: Programming Fundamentals0-0-3-1CS101
2CS201Data Structures and Algorithms3-0-0-3CS101
2CS202Discrete Mathematics3-0-0-3CS102
2CS203Object-Oriented Programming3-0-0-3CS101
2CS204Database Management Systems3-0-0-3CS201
2CS205Operating Systems3-0-0-3CS201
2CS206Lab: Data Structures and Algorithms0-0-3-1CS201
3CS301Software Engineering3-0-0-3CS203
3CS302Computer Networks3-0-0-3CS205
3CS303Compiler Design3-0-0-3CS201
3CS304Artificial Intelligence3-0-0-3CS202
3CS305Human-Computer Interaction3-0-0-3CS203
3CS306Lab: Software Engineering0-0-3-1CS301
4CS401Machine Learning3-0-0-3CS304
4CS402Cybersecurity3-0-0-3CS205
4CS403Big Data Analytics3-0-0-3CS301
4CS404Cloud Computing3-0-0-3CS302
4CS405Embedded Systems3-0-0-3CS205
4CS406Lab: Machine Learning0-0-3-1CS401
5CS501Advanced Data Structures3-0-0-3CS201
5CS502Computer Vision3-0-0-3CS401
5CS503Neural Networks3-0-0-3CS401
5CS504Information Retrieval3-0-0-3CS304
5CS505Database Systems3-0-0-3CS204
5CS506Lab: Computer Vision0-0-3-1CS502
6CS601Research Methodology3-0-0-3CS301
6CS602Special Topics in AI3-0-0-3CS401
6CS603Software Testing3-0-0-3CS301
6CS604Mobile Computing3-0-0-3CS302
6CS605Internet of Things3-0-0-3CS205
6CS606Lab: Software Testing0-0-3-1CS603
7CS701Capstone Project3-0-0-3CS301
7CS702Internship0-0-0-3CS601
8CS801Thesis3-0-0-3CS701
8CS802Advanced Topics in Computer Science3-0-0-3CS401

The department's philosophy on project-based learning is centered on the belief that hands-on experience is essential for developing practical skills and deep understanding. Students are required to complete both mini-projects and a final-year thesis/capstone project. The mini-projects are designed to provide students with early exposure to real-world challenges and to develop their problem-solving and teamwork skills.

The final-year thesis/capstone project is a significant component of the program, allowing students to apply their knowledge to a substantial research or development task. Students work closely with faculty mentors to select a project topic, develop a project plan, and execute the project over a period of several months. The project is evaluated based on multiple criteria, including technical depth, innovation, presentation, and documentation.

Students are encouraged to select projects that align with their interests and career goals. The department provides a list of potential project topics, and students can also propose their own ideas in consultation with faculty members. Faculty mentors are assigned based on the student's interests and the mentor's expertise, ensuring that students receive appropriate guidance throughout their project journey.

Advanced Departmental Elective Courses

Advanced departmental elective courses are designed to provide students with in-depth knowledge in specialized areas of computer science. These courses are offered in the later semesters and are taught by faculty members who are leaders in their respective fields. The following are detailed descriptions of several advanced elective courses:

Artificial Intelligence

This course covers the fundamental concepts and techniques of artificial intelligence, including search algorithms, knowledge representation, reasoning, and machine learning. Students learn to design and implement intelligent systems that can solve complex problems. The course emphasizes both theoretical foundations and practical applications, with hands-on projects that allow students to experiment with AI techniques.

Cybersecurity

This course provides a comprehensive overview of cybersecurity principles and practices. Students learn about network security, cryptography, ethical hacking, and risk management. The course includes practical labs where students can apply security techniques to real-world scenarios. Students also explore emerging threats and defense mechanisms in the evolving cybersecurity landscape.

Software Engineering

This course focuses on the systematic approach to software development, including requirements analysis, design, implementation, testing, and maintenance. Students learn about software architecture, project management, and agile methodologies. The course emphasizes the importance of quality assurance and the role of software engineering in developing robust and scalable systems.

Data Science and Analytics

This course introduces students to the principles and practices of data science, including data mining, statistical analysis, and predictive modeling. Students learn to use tools and techniques for extracting insights from large datasets. The course also covers visualization techniques and the ethical considerations in data science.

Human-Computer Interaction

This course explores the design and evaluation of interactive systems. Students study user experience design, usability testing, and human factors in computing. The course includes hands-on projects where students design and test interfaces for various applications. The goal is to develop systems that are intuitive, efficient, and user-friendly.

Computer Graphics and Visualization

This course covers the principles and techniques of computer graphics and visualization. Students learn about 3D modeling, animation, and rendering. The course includes practical labs where students can create visual representations of data and concepts. Students also explore the applications of computer graphics in entertainment, education, and scientific visualization.

Database Systems

This course provides an in-depth study of database systems, including design, implementation, and management. Students learn about relational databases, indexing, query optimization, and transaction processing. The course also covers advanced topics such as distributed databases and data warehousing.

Network Security

This course focuses on securing communication networks and protecting data in transit. Students study network protocols, intrusion detection, and secure communication. The course includes practical labs where students can implement security measures and evaluate their effectiveness. The goal is to develop robust security frameworks for large-scale networks.

Embedded Systems

This course covers the design and implementation of embedded systems, which are specialized computing systems embedded in larger devices. Students learn about hardware-software integration, real-time systems, and system-on-chip design. The course includes practical labs where students can build and test embedded systems.

Cloud Computing

This course provides a comprehensive overview of cloud computing technologies and services. Students learn about virtualization, distributed systems, and cloud architecture. The course also covers cloud security, management, and cost optimization. Students gain hands-on experience with popular cloud platforms and tools.