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.
Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
---|---|---|---|---|
1 | CS101 | Engineering Mathematics I | 3-1-0-4 | - |
1 | CS102 | Physics for Computing | 3-1-0-4 | - |
1 | CS103 | Introduction to Programming | 3-1-0-4 | - |
1 | CS104 | Computer Organization and Architecture | 3-1-0-4 | - |
1 | CS105 | English for Technical Communication | 2-0-0-2 | - |
1 | CS106 | Workshop on Programming | 0-0-3-1 | - |
2 | CS201 | Engineering Mathematics II | 3-1-0-4 | CS101 |
2 | CS202 | Data Structures and Algorithms | 3-1-0-4 | CS103 |
2 | CS203 | Digital Logic and Design | 3-1-0-4 | - |
2 | CS204 | Database Management Systems | 3-1-0-4 | CS103 |
2 | CS205 | Object Oriented Programming | 3-1-0-4 | CS103 |
2 | CS206 | Programming Lab | 0-0-3-1 | CS103 |
3 | CS301 | Engineering Mathematics III | 3-1-0-4 | CS201 |
3 | CS302 | Software Engineering | 3-1-0-4 | CS205 |
3 | CS303 | Computer Networks | 3-1-0-4 | CS204 |
3 | CS304 | Operating Systems | 3-1-0-4 | CS204 |
3 | CS305 | Web Technologies | 3-1-0-4 | CS205 |
3 | CS306 | Systems Programming Lab | 0-0-3-1 | CS204 |
4 | CS401 | Engineering Mathematics IV | 3-1-0-4 | CS301 |
4 | CS402 | Artificial Intelligence and Machine Learning | 3-1-0-4 | CS202 |
4 | CS403 | Cybersecurity Fundamentals | 3-1-0-4 | CS303 |
4 | CS404 | Data Structures and Algorithms Lab | 0-0-3-1 | CS202 |
4 | CS405 | Software Project Management | 3-1-0-4 | CS302 |
4 | CS406 | Mini Project I | 0-0-6-2 | - |
5 | CS501 | Data Analytics and Big Data | 3-1-0-4 | CS402 |
5 | CS502 | Mobile Application Development | 3-1-0-4 | CS305 |
5 | CS503 | Human Computer Interaction | 3-1-0-4 | CS305 |
5 | CS504 | Internet of Things | 3-1-0-4 | CS303 |
5 | CS505 | Blockchain Technology | 3-1-0-4 | - |
5 | CS506 | Mini Project II | 0-0-6-2 | - |
6 | CS601 | Advanced Machine Learning | 3-1-0-4 | CS402 |
6 | CS602 | Cloud Computing | 3-1-0-4 | CS303 |
6 | CS603 | Game Development | 3-1-0-4 | CS305 |
6 | CS604 | Research Methodology | 2-0-0-2 | - |
6 | CS605 | Capstone Project I | 0-0-9-3 | - |
6 | CS606 | Elective Course I | 3-1-0-4 | - |
7 | CS701 | Advanced Cybersecurity | 3-1-0-4 | CS403 |
7 | CS702 | Deep Learning and Neural Networks | 3-1-0-4 | CS601 |
7 | CS703 | Big Data Analytics | 3-1-0-4 | CS501 |
7 | CS704 | Capstone Project II | 0-0-9-3 | - |
7 | CS705 | Elective Course II | 3-1-0-4 | - |
7 | CS706 | Elective Course III | 3-1-0-4 | - |
8 | CS801 | Capstone Project III | 0-0-9-3 | - |
8 | CS802 | Elective Course IV | 3-1-0-4 | - |
8 | CS803 | Elective Course V | 3-1-0-4 | - |
8 | CS804 | Internship | 0-0-0-6 | - |
8 | CS805 | Professional Ethics and Communication | 2-0-0-2 | - |
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.