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Pune, Maharashtra, India

Duration

4 Years

Computer Applications

Dayananda Sagar University, Bangalore
Duration
4 Years
Computer Applications UG OFFLINE

Duration

4 Years

Computer Applications

Dayananda Sagar University, Bangalore
Duration
Apply

Fees

₹3,00,000

Placement

92.0%

Avg Package

₹5,00,000

Highest Package

₹8,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Computer Applications
UG
OFFLINE

Fees

₹3,00,000

Placement

92.0%

Avg Package

₹5,00,000

Highest Package

₹8,00,000

Seats

120

Students

1,200

ApplyCollege

Seats

120

Students

1,200

Curriculum

Curriculum Overview

The Computer Applications program at Dayananda Sagar University Bangalore follows a structured and progressive curriculum designed to build strong foundational knowledge and advanced technical skills. The program spans eight semesters, with each semester carrying specific credit requirements and subject distributions.

Course Structure Table

Semester Course Code Course Title L-T-P-C Pre-requisites
1 CS101 Engineering Mathematics I 3-0-0-3 -
1 CS102 Physics for Computer Science 3-0-0-3 -
1 CS103 Chemistry for Engineering 3-0-0-3 -
1 CS104 Introduction to Programming 2-0-2-3 -
1 CS105 English for Communication 2-0-0-2 -
1 CS106 Computer Graphics Lab 0-0-3-2 -
2 CS201 Engineering Mathematics II 3-0-0-3 CS101
2 CS202 Data Structures and Algorithms 3-0-0-3 CS104
2 CS203 Digital Logic and Computer Organization 3-0-0-3 -
2 CS204 Object-Oriented Programming with Java 2-0-2-3 CS104
2 CS205 Electronics for Computer Science 3-0-0-3 -
2 CS206 Data Structures Lab 0-0-3-2 CS202
3 CS301 Database Management Systems 3-0-0-3 CS202
3 CS302 Operating Systems 3-0-0-3 CS203
3 CS303 Computer Networks 3-0-0-3 CS205
3 CS304 Software Engineering 3-0-0-3 CS202
3 CS305 Web Technologies 2-0-2-3 CS204
3 CS306 Database Lab 0-0-3-2 CS301
4 CS401 Design and Analysis of Algorithms 3-0-0-3 CS202
4 CS402 Artificial Intelligence and Machine Learning 3-0-0-3 CS301
4 CS403 Cybersecurity Fundamentals 3-0-0-3 CS302
4 CS404 Data Science and Analytics 3-0-0-3 CS301
4 CS405 Mobile Application Development 2-0-2-3 CS204
4 CS406 AI and ML Lab 0-0-3-2 CS402
5 CS501 Cloud Computing and DevOps 3-0-0-3 CS402
5 CS502 Internet of Things (IoT) 3-0-0-3 CS303
5 CS503 Human-Computer Interaction 3-0-0-3 CS204
5 CS504 Game Development 2-0-2-3 CS204
5 CS505 Embedded Systems 3-0-0-3 CS203
5 CS506 IoT Lab 0-0-3-2 CS502
6 CS601 Advanced Topics in AI and ML 3-0-0-3 CS402
6 CS602 Blockchain Technologies 3-0-0-3 CS403
6 CS603 Big Data Analytics 3-0-0-3 CS404
6 CS604 Mobile App Development Lab 0-0-3-2 CS504
7 CS701 Capstone Project I 2-0-0-4 -
7 CS702 Research Methodology 2-0-0-2 -
8 CS801 Capstone Project II 2-0-0-4 CS701

Detailed Departmental Elective Courses

The following advanced departmental electives provide specialized knowledge and skills to students:

  • Deep Learning with TensorFlow: This course explores deep neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) using TensorFlow 2.x. Students learn to implement models for image recognition, natural language processing, and time series forecasting.
  • Blockchain Technologies: Covers distributed ledgers, smart contracts, cryptocurrency systems, and decentralized applications (dApps). Students build practical blockchain solutions using Ethereum and Hyperledger frameworks.
  • Internet of Things (IoT) and Embedded Systems: Focuses on connecting physical devices to the internet, designing embedded controllers, and managing sensor networks. Includes hands-on projects involving Arduino, Raspberry Pi, and ESP32 platforms.
  • Software Engineering Principles: Covers software architecture, testing strategies, version control systems, and agile methodologies. Students apply industry-standard tools like JIRA, GitLab, and Jenkins to manage complex software development projects.
  • Game Development: Teaches game design principles, 3D modeling, animation techniques, and scripting using Unity or Unreal Engine. Projects include creating interactive games for PC, mobile, and VR platforms.
  • Cybersecurity in Practice: Provides practical experience in ethical hacking, penetration testing, network security, and incident response. Students conduct simulations of real-world attacks and defend against them using industry-standard tools like Metasploit and Wireshark.
  • Data Science and Big Data Analytics: Focuses on extracting insights from large datasets using statistical methods and predictive modeling. Includes hands-on experience with Hadoop, Spark, Python libraries (Pandas, Scikit-learn), and cloud platforms like AWS and GCP.
  • Cloud Computing and DevOps: Covers cloud architecture, containerization using Docker, orchestration with Kubernetes, and deployment automation. Students deploy applications to AWS, Azure, and Google Cloud Platform environments.
  • Mobile Application Development: Teaches cross-platform app development using frameworks like Flutter, React Native, and Xamarin. Projects include building apps for iOS and Android devices with modern UI/UX principles.
  • Human-Computer Interaction: Explores user experience design, usability testing, and interaction design principles. Students prototype interfaces using Figma, Sketch, and Adobe XD, and evaluate them through user research methods.

Project-Based Learning Philosophy

The department believes in the power of experiential learning through project-based education. Students are encouraged to apply theoretical concepts to real-world challenges throughout their academic journey. The approach fosters critical thinking, teamwork, and innovation skills essential for future professionals.

Mini-Projects (First Year)

Students work on small-scale projects in their first year, focusing on basic programming concepts, data structures, and simple software development tasks. Projects are typically completed within one semester and evaluated based on design, implementation, and documentation quality.

Final-Year Capstone Project

The capstone project is a significant undertaking that spans two semesters (7th and 8th). Students select topics aligned with their interests or industry needs, often collaborating with faculty members or external partners. The project involves:

  • Problem identification and scoping
  • Research and literature review
  • Design and prototyping
  • Implementation and testing
  • Documentation and presentation

Students receive guidance from assigned faculty mentors and must present their work at a final showcase event open to industry experts, faculty, and peers. Successful projects often lead to patents, publications, or commercialization opportunities.