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Pune, Maharashtra, India

Duration

4 Years

Computer Applications

Poornima University Jaipur
Duration
4 Years
Computer Applications UG OFFLINE

Duration

4 Years

Computer Applications

Poornima University Jaipur
Duration
Apply

Fees

₹6,00,000

Placement

94.5%

Avg Package

₹5,20,000

Highest Package

₹8,50,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Computer Applications
UG
OFFLINE

Fees

₹6,00,000

Placement

94.5%

Avg Package

₹5,20,000

Highest Package

₹8,50,000

Seats

120

Students

300

ApplyCollege

Seats

120

Students

300

Curriculum

Comprehensive Course Structure

The Computer Applications program at Poornima University Jaipur is structured over 8 semesters, providing a progressive and comprehensive learning experience that builds upon foundational knowledge while enabling specialization in advanced domains. The curriculum is designed to ensure students develop both theoretical understanding and practical skills necessary for success in the technology industry.

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Pre-requisites
1CS101Engineering Mathematics I3-1-0-4-
1CS102Physics for Computing3-1-0-4-
1CS103Introduction to Programming3-1-0-4-
1CS104Computer Organization and Architecture3-1-0-4-
1CS105English for Technical Communication2-0-0-2-
1CS106Workshop on Programming0-0-3-1-
2CS201Engineering Mathematics II3-1-0-4CS101
2CS202Data Structures and Algorithms3-1-0-4CS103
2CS203Digital Logic and Design3-1-0-4-
2CS204Database Management Systems3-1-0-4CS103
2CS205Object Oriented Programming3-1-0-4CS103
2CS206Programming Lab0-0-3-1CS103
3CS301Engineering Mathematics III3-1-0-4CS201
3CS302Software Engineering3-1-0-4CS205
3CS303Computer Networks3-1-0-4CS204
3CS304Operating Systems3-1-0-4CS204
3CS305Web Technologies3-1-0-4CS205
3CS306Systems Programming Lab0-0-3-1CS204
4CS401Engineering Mathematics IV3-1-0-4CS301
4CS402Artificial Intelligence and Machine Learning3-1-0-4CS202
4CS403Cybersecurity Fundamentals3-1-0-4CS303
4CS404Data Structures and Algorithms Lab0-0-3-1CS202
4CS405Software Project Management3-1-0-4CS302
4CS406Mini Project I0-0-6-2-
5CS501Data Analytics and Big Data3-1-0-4CS402
5CS502Mobile Application Development3-1-0-4CS305
5CS503Human Computer Interaction3-1-0-4CS305
5CS504Internet of Things3-1-0-4CS303
5CS505Blockchain Technology3-1-0-4-
5CS506Mini Project II0-0-6-2-
6CS601Advanced Machine Learning3-1-0-4CS402
6CS602Cloud Computing3-1-0-4CS303
6CS603Game Development3-1-0-4CS305
6CS604Research Methodology2-0-0-2-
6CS605Capstone Project I0-0-9-3-
6CS606Elective Course I3-1-0-4-
7CS701Advanced Cybersecurity3-1-0-4CS403
7CS702Deep Learning and Neural Networks3-1-0-4CS601
7CS703Big Data Analytics3-1-0-4CS501
7CS704Capstone Project II0-0-9-3-
7CS705Elective Course II3-1-0-4-
7CS706Elective Course III3-1-0-4-
8CS801Capstone Project III0-0-9-3-
8CS802Elective Course IV3-1-0-4-
8CS803Elective Course V3-1-0-4-
8CS804Internship0-0-0-6-
8CS805Professional Ethics and Communication2-0-0-2-

Advanced Departmental Elective Courses

Departmental electives provide students with opportunities to explore specialized areas within Computer Applications, building upon the foundational knowledge gained in core courses. These advanced courses are designed to offer in-depth insights into emerging technologies and industry trends.

Artificial Intelligence and Machine Learning

This course delves deep into the principles and techniques of artificial intelligence and machine learning, providing students with hands-on experience in developing intelligent systems. The curriculum covers supervised and unsupervised learning algorithms, neural networks, deep learning frameworks, and natural language processing. Students will work on real-world projects involving computer vision, speech recognition, and predictive analytics.

The course emphasizes both theoretical understanding and practical implementation using popular frameworks such as TensorFlow, PyTorch, and scikit-learn. Through laboratory sessions and project work, students develop skills in model training, evaluation, and deployment. The course also introduces ethical considerations in AI development and discusses the societal impact of artificial intelligence systems.

Data Analytics and Big Data

This elective focuses on extracting meaningful insights from large datasets using advanced analytical techniques and big data technologies. Students learn to work with distributed computing frameworks such as Apache Hadoop and Spark, and gain expertise in data mining, statistical analysis, and predictive modeling. The course covers both structured and unstructured data processing, including text analytics and sentiment analysis.

Laboratory sessions provide hands-on experience with real-world datasets from various domains, allowing students to apply their knowledge to practical problems. The curriculum includes advanced topics such as machine learning for big data, graph analytics, and real-time data processing. Students will also explore the business applications of data analytics and learn to communicate findings effectively to stakeholders.

Cybersecurity Fundamentals

This course provides a comprehensive introduction to cybersecurity principles and practices, covering essential topics such as network security, cryptography, digital forensics, and risk management. Students will learn about common attack vectors, security protocols, and defensive strategies used to protect digital assets. The curriculum includes hands-on laboratory exercises using industry-standard tools and techniques.

The course emphasizes both theoretical concepts and practical implementation, with students gaining experience in penetration testing, vulnerability assessment, and incident response. Students will also explore emerging threats in the cybersecurity landscape and learn about regulatory compliance requirements for security implementations.

Mobile Application Development

This elective focuses on developing cross-platform mobile applications for iOS and Android devices. Students learn to use modern frameworks such as React Native, Flutter, and Xamarin, along with backend technologies for cloud integration. The curriculum covers user interface design, application architecture, and deployment strategies for mobile platforms.

Laboratory sessions provide hands-on experience in building functional mobile applications from concept to deployment. Students will work on projects involving real-world scenarios such as e-commerce applications, social networking platforms, and productivity tools. The course also covers app store optimization, performance tuning, and user experience considerations.

Web Technologies

This course explores the development of dynamic web applications using modern frontend and backend technologies. Students learn to create responsive websites with interactive features using HTML5, CSS3, JavaScript, and modern frameworks such as React and Angular. The curriculum covers server-side scripting, database integration, and cloud deployment strategies.

Students will gain experience in building full-stack web applications that can handle concurrent users and complex data interactions. Laboratory sessions include projects on e-commerce platforms, content management systems, and social networking websites. The course also addresses security considerations in web development and performance optimization techniques.

Human-Computer Interaction

This elective focuses on designing user-friendly interfaces and improving the overall user experience of digital products. Students learn about usability testing, interaction design, prototyping, and user research methods. The curriculum includes topics such as cognitive psychology, accessibility design, and mobile interface design.

Laboratory sessions provide hands-on experience in conducting user studies, creating wireframes and prototypes, and evaluating interfaces for usability. Students will work on projects involving real-world applications such as mobile apps, web platforms, and interactive systems. The course emphasizes the importance of user-centered design principles in modern software development.

Internet of Things (IoT)

This course explores the integration of physical devices with internet connectivity to create smart systems and applications. Students learn about sensor networks, embedded systems programming, cloud integration, and smart city applications. The curriculum covers both hardware and software aspects of IoT systems, including device communication protocols and data processing techniques.

Laboratory sessions provide hands-on experience in building IoT prototypes using platforms such as Arduino, Raspberry Pi, and ESP32. Students will work on projects involving smart home automation, environmental monitoring, and industrial IoT applications. The course also addresses security considerations and scalability challenges in IoT deployments.

Blockchain Technology

This elective introduces students to distributed ledger technology and its applications in various industries. Students learn to develop blockchain-based applications, understand consensus mechanisms, and explore smart contract development. The curriculum covers both theoretical concepts and practical implementation of blockchain systems.

Laboratory sessions provide hands-on experience in building blockchain applications using platforms such as Ethereum and Hyperledger Fabric. Students will work on projects involving cryptocurrency development, supply chain tracking, and decentralized applications (DApps). The course also addresses the regulatory and ethical considerations surrounding blockchain technology.

Game Development

This course prepares students for careers in the gaming industry by teaching game design principles, 3D modeling, animation techniques, and real-time rendering engines. Students gain experience with popular game development platforms such as Unity and Unreal Engine. The curriculum includes topics such as game mechanics, user interface design, and performance optimization.

Laboratory sessions provide hands-on experience in creating functional game prototypes from concept to completion. Students will work on projects involving different genres of games such as puzzle games, action-adventure titles, and strategy games. The course also addresses the business aspects of game development including monetization strategies and marketing approaches.

Advanced Machine Learning

This advanced elective delves into specialized topics in machine learning, including reinforcement learning, deep learning architectures, and transfer learning techniques. Students will explore cutting-edge research papers and develop skills in implementing complex algorithms using modern frameworks. The course emphasizes both theoretical understanding and practical application through hands-on projects.

Laboratory sessions provide opportunities to work on advanced research problems and collaborate with faculty members on ongoing projects. Students will gain experience in developing novel machine learning solutions for real-world challenges, including natural language processing, computer vision, and robotics applications.

Cloud Computing

This course provides comprehensive coverage of cloud computing technologies and services, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Students learn to design and deploy scalable applications using major cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform.

Laboratory sessions provide hands-on experience in cloud architecture design, security implementation, and performance optimization. Students will work on projects involving migration of existing systems to the cloud, development of cloud-native applications, and implementation of microservices architectures. The course also addresses cost management and regulatory compliance considerations in cloud deployments.

Project-Based Learning Philosophy

The department's philosophy on project-based learning is centered on providing students with authentic learning experiences that mirror real-world challenges. This approach emphasizes collaboration, critical thinking, and the application of theoretical knowledge to practical problems.

Mini-projects are assigned in the third and fifth semesters, allowing students to apply concepts learned in core courses to hands-on applications. These projects are designed to be manageable yet challenging, providing students with opportunities to develop problem-solving skills and technical competencies. Students work in teams, fostering collaboration and communication skills essential for professional success.

The final-year capstone project represents the culmination of a student's academic journey, requiring them to integrate knowledge from multiple domains and develop comprehensive solutions to complex problems. This project is often sponsored by industry partners, providing students with exposure to real-world applications and potential career opportunities.

Project selection involves a structured process where students propose topics based on their interests and faculty expertise. Faculty mentors are assigned based on the alignment of student interests with departmental strengths and research areas. Students have access to resources such as laboratory facilities, software licenses, and expert guidance throughout the project development process.

Evaluation criteria for projects include technical implementation, innovation, presentation quality, and documentation standards. Regular progress reviews ensure that projects stay on track and meet academic expectations. The department also encourages students to present their work at conferences and competitions, providing opportunities for recognition and networking with industry professionals.