Curriculum Overview
The Computer Applications program at Ajeenkya D Y Patil University Pune is designed to provide a comprehensive educational experience that combines foundational knowledge with specialized skills. The curriculum is divided into eight semesters, with each semester offering a mix of core subjects, departmental electives, science electives, and laboratory sessions.
Course Schedule
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming | 3-0-0-3 | - |
| 1 | CS102 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| 1 | MA101 | Mathematics for Computer Applications | 3-0-0-3 | - |
| 1 | PH101 | Physics for Computer Science | 3-0-0-3 | - |
| 1 | HS101 | English Communication | 2-0-0-2 | - |
| 2 | CS201 | Object-Oriented Programming with Java | 3-0-0-3 | CS101 |
| 2 | CS202 | Database Management Systems | 3-0-0-3 | CS102 |
| 2 | CS203 | Operating Systems | 3-0-0-3 | CS102 |
| 2 | MA201 | Probability and Statistics | 3-0-0-3 | MA101 |
| 2 | PH201 | Electronic Devices and Circuits | 3-0-0-3 | PH101 |
| 3 | CS301 | Computer Networks | 3-0-0-3 | CS203 |
| 3 | CS302 | Software Engineering | 3-0-0-3 | CS201 |
| 3 | CS303 | Artificial Intelligence and Machine Learning | 3-0-0-3 | CS202 |
| 3 | CS304 | Cryptography and Network Security | 3-0-0-3 | CS301 |
| 3 | MA301 | Linear Algebra and Numerical Methods | 3-0-0-3 | MA201 |
| 4 | CS401 | Cloud Computing and DevOps | 3-0-0-3 | CS301 |
| 4 | CS402 | Data Science and Analytics | 3-0-0-3 | CS303 |
| 4 | CS403 | Mobile Application Development | 3-0-0-3 | CS201 |
| 4 | CS404 | Web Technologies | 3-0-0-3 | CS201 |
| 4 | MA401 | Optimization Techniques | 3-0-0-3 | MA301 |
| 5 | CS501 | Advanced Machine Learning | 3-0-0-3 | CS303 |
| 5 | CS502 | Big Data Technologies | 3-0-0-3 | CS402 |
| 5 | CS503 | Human-Computer Interaction | 3-0-0-3 | CS404 |
| 5 | CS504 | Embedded Systems | 3-0-0-3 | CS301 |
| 5 | MA501 | Stochastic Processes | 3-0-0-3 | MA401 |
| 6 | CS601 | Research Methodology | 3-0-0-3 | - |
| 6 | CS602 | Capstone Project | 3-0-0-3 | CS501 |
| 6 | CS603 | Internship | 3-0-0-3 | - |
| 6 | CS604 | Special Topics in Computer Applications | 3-0-0-3 | CS502 |
| 6 | MA601 | Advanced Mathematics for Computing | 3-0-0-3 | MA501 |
| 7 | CS701 | Specialization Elective 1 | 3-0-0-3 | - |
| 7 | CS702 | Specialization Elective 2 | 3-0-0-3 | - |
| 7 | CS703 | Specialization Elective 3 | 3-0-0-3 | - |
| 7 | CS704 | Specialization Elective 4 | 3-0-0-3 | - |
| 7 | MA701 | Advanced Numerical Methods | 3-0-0-3 | MA601 |
| 8 | CS801 | Industry Project | 3-0-0-3 | CS602 |
| 8 | CS802 | Professional Ethics and Sustainability | 2-0-0-2 | - |
| 8 | CS803 | Final Year Project | 3-0-0-3 | CS602 |
| 8 | CS804 | Advanced Research Topics | 3-0-0-3 | - |
| 8 | MA801 | Mathematical Modeling | 3-0-0-3 | MA701 |
Advanced Departmental Electives
The department offers several advanced elective courses that allow students to explore specialized areas within Computer Applications. These courses are designed to keep pace with the latest developments in technology and industry practices.
Advanced Machine Learning
This course delves deep into advanced topics such as reinforcement learning, generative adversarial networks (GANs), transformers, and attention mechanisms. Students learn how to implement complex models using frameworks like TensorFlow and PyTorch. The course includes hands-on labs where students work on real-world datasets from Kaggle and industry partners.
Big Data Technologies
This elective introduces students to big data processing frameworks such as Apache Spark, Hadoop, and Kafka. Students gain experience in distributed computing environments and learn how to design scalable solutions for handling large volumes of data. The course also covers data warehousing concepts and NoSQL databases like MongoDB and Cassandra.
Human-Computer Interaction
Focusing on user-centered design principles, this course explores the psychology behind interface design, usability testing methodologies, and accessibility standards. Students learn to create intuitive, inclusive products that enhance user satisfaction. The course includes collaborative projects with design teams from local startups.
Embedded Systems
This elective provides an overview of embedded system architectures, real-time operating systems, and microcontroller programming. Students work on projects involving IoT devices, sensor integration, and low-power computing solutions. The labs use platforms like Arduino and Raspberry Pi for practical experimentation.
Research Methodology
Designed to prepare students for graduate-level research, this course covers statistical analysis, experimental design, literature review techniques, and academic writing skills. Students are introduced to ethical considerations in research and learn how to present findings effectively through posters and presentations.
Project-Based Learning Philosophy
The department places a strong emphasis on project-based learning as a core component of the curriculum. Projects are structured to mirror real-world challenges faced by industry professionals, ensuring that students gain practical experience in problem-solving and innovation.
Mini-Projects
Mini-projects are assigned throughout the program to reinforce classroom learning and encourage experimentation. These projects typically span 2-3 weeks and involve working on small-scale applications or research questions. Students are grouped into teams and guided by faculty mentors who provide regular feedback and support.
Final-Year Thesis/Capstone Project
The final-year capstone project is a significant milestone that allows students to apply their knowledge to solve complex problems. Students choose a topic aligned with their interests or industry needs, working closely with a faculty advisor throughout the process. The project involves extensive research, implementation, and documentation, culminating in a presentation at the annual university symposium.
Project Selection and Mentorship
Students select their projects based on their academic interests, career goals, or industry connections. Faculty members from various specializations serve as mentors, providing guidance on research methodologies, technical challenges, and project execution. The department maintains a database of potential project ideas sourced from industry partners, faculty research initiatives, and student proposals.