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Fees
₹8,00,000
Placement
92.5%
Avg Package
₹5,60,000
Highest Package
₹8,50,000
Fees
₹8,00,000
Placement
92.5%
Avg Package
₹5,60,000
Highest Package
₹8,50,000
Seats
120
Students
1,200
Seats
120
Students
1,200
The Computer Applications program at Pes University Bangalore is meticulously structured to ensure a progressive and well-rounded educational experience. The curriculum spans 8 semesters, with each semester comprising core courses, departmental electives, science electives, and laboratory sessions.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | CS102 | Physics for Computer Science | 3-1-0-4 | - |
| 1 | CS103 | Introduction to Programming | 3-0-2-5 | - |
| 1 | CS104 | Computer Fundamentals | 2-0-2-4 | - |
| 1 | CS105 | Communication Skills | 2-0-0-2 | - |
| 2 | CS201 | Engineering Mathematics II | 3-1-0-4 | CS101 |
| 2 | CS202 | Object-Oriented Programming | 3-0-2-5 | CS103 |
| 2 | CS203 | Data Structures and Algorithms | 3-0-2-5 | CS103 |
| 2 | CS204 | Digital Logic Design | 3-1-0-4 | - |
| 2 | CS205 | Database Management Systems | 3-0-2-5 | CS103 |
| 3 | CS301 | Operating Systems | 3-0-2-5 | CS202 |
| 3 | CS302 | Computer Networks | 3-0-2-5 | CS204 |
| 3 | CS303 | Software Engineering | 3-0-2-5 | CS203 |
| 3 | CS304 | Web Technologies | 3-0-2-5 | CS202 |
| 3 | CS305 | Probability and Statistics | 3-1-0-4 | CS101 |
| 4 | CS401 | Machine Learning | 3-0-2-5 | CS305 |
| 4 | CS402 | Cybersecurity | 3-0-2-5 | CS204 |
| 4 | CS403 | Cloud Computing | 3-0-2-5 | CS302 |
| 4 | CS404 | Mobile Application Development | 3-0-2-5 | CS202 |
| 4 | CS405 | Human-Computer Interaction | 3-0-2-5 | CS203 |
| 5 | CS501 | Advanced Data Structures | 3-0-2-5 | CS203 |
| 5 | CS502 | Artificial Intelligence | 3-0-2-5 | CS401 |
| 5 | CS503 | Internet of Things | 3-0-2-5 | CS302 |
| 5 | CS504 | Big Data Analytics | 3-0-2-5 | CS305 |
| 5 | CS505 | Embedded Systems | 3-0-2-5 | CS204 |
| 6 | CS601 | Capstone Project I | 0-0-6-8 | CS301, CS303 |
| 6 | CS602 | Specialized Elective I | 3-0-2-5 | - |
| 6 | CS603 | Specialized Elective II | 3-0-2-5 | - |
| 6 | CS604 | Internship | 0-0-0-0 | - |
| 7 | CS701 | Capstone Project II | 0-0-6-8 | CS601 |
| 7 | CS702 | Research Methodology | 3-0-2-5 | - |
| 7 | CS703 | Specialized Elective III | 3-0-2-5 | - |
| 7 | CS704 | Specialized Elective IV | 3-0-2-5 | - |
| 8 | CS801 | Final Project | 0-0-6-8 | CS701 |
| 8 | CS802 | Elective Course | 3-0-2-5 | - |
| 8 | CS803 | Professional Ethics | 2-0-0-2 | - |
The department offers several advanced elective courses designed to provide in-depth knowledge and practical skills in specialized areas. These courses are developed based on industry trends and research advancements.
This course explores the principles of machine learning algorithms, including supervised, unsupervised, and reinforcement learning techniques. Students will learn how to implement these algorithms using Python and TensorFlow, and apply them to real-world datasets.
Students are introduced to various cybersecurity frameworks, threat modeling, and risk assessment methodologies. The course covers encryption, network security protocols, and ethical hacking practices, preparing students for careers in digital security.
This elective delves into cloud architecture, virtualization, and service models such as IaaS, PaaS, and SaaS. Students will gain hands-on experience with AWS, Azure, and GCP platforms through lab sessions and project work.
The course focuses on developing cross-platform mobile applications using frameworks like React Native and Flutter. Students will build apps for both iOS and Android platforms, ensuring compatibility and performance optimization.
This course emphasizes the design and evaluation of interactive systems. It covers usability testing, prototyping, and user experience (UX) design principles to create intuitive interfaces that enhance user satisfaction.
Students will learn to process and analyze large volumes of data using tools like Hadoop, Spark, and NoSQL databases. The course includes practical applications in business intelligence, predictive analytics, and data visualization.
This elective explores the integration of computing devices into everyday objects to enable communication and data exchange. Topics include sensor networks, embedded systems programming, and smart city applications.
The course provides a comprehensive overview of embedded system design, including microcontroller architecture, real-time operating systems (RTOS), and hardware-software co-design principles.
The department strongly believes in project-based learning as a means to bridge the gap between theory and practice. This approach ensures that students gain hands-on experience while working on meaningful, industry-relevant projects.
Mini-projects are assigned during the second and third years of the program. These projects are typically completed in teams of 3-5 members and must address a real-world problem or challenge. Projects are evaluated based on technical execution, innovation, documentation quality, and presentation skills.
The final-year capstone project is a comprehensive endeavor that requires students to demonstrate their mastery of the field. Students work under the guidance of faculty mentors to develop an innovative solution or research study. The project culminates in a final presentation and a detailed report submitted to the department.
Each student is paired with a faculty mentor who provides academic support, career guidance, and feedback on their projects. Faculty mentors are selected based on their expertise and availability, ensuring personalized attention for each student.
