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Fees
₹2,50,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Fees
₹2,50,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Seats
120
Students
350
Seats
120
Students
350
The Computer Applications program at Mohan Babu University Tirupati follows a rigorous, semester-based academic calendar spanning 8 semesters over four years. Each semester includes core courses, departmental electives, science electives, and laboratory sessions designed to provide a balanced mix of theoretical knowledge and practical application.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming | 3-0-0-3 | - |
| 1 | CS102 | Mathematics for Computer Applications | 3-0-0-3 | - |
| 1 | CS103 | Physics of Computing | 3-0-0-3 | - |
| 1 | CS104 | Computer Organization and Architecture | 3-0-0-3 | - |
| 1 | CS105 | English for Technical Communication | 2-0-0-2 | - |
| 1 | CS106 | Introduction to Data Structures and Algorithms | 3-0-0-3 | - |
| 1 | CS107 | Programming Lab | 0-0-2-1 | - |
| 1 | CS108 | Data Structures and Algorithms Lab | 0-0-2-1 | - |
| 2 | CS201 | Database Management Systems | 3-0-0-3 | CS101, CS106 |
| 2 | CS202 | Object-Oriented Programming | 3-0-0-3 | CS101 |
| 2 | CS203 | Discrete Mathematics | 3-0-0-3 | - |
| 2 | CS204 | Computer Networks | 3-0-0-3 | CS103, CS104 |
| 2 | CS205 | Web Technologies | 3-0-0-3 | CS101 |
| 2 | CS206 | Probability and Statistics | 3-0-0-3 | - |
| 2 | CS207 | OOP Lab | 0-0-2-1 | CS101 |
| 2 | CS208 | Web Technologies Lab | 0-0-2-1 | CS101, CS205 |
| 3 | CS301 | Operating Systems | 3-0-0-3 | CS104, CS202 |
| 3 | CS302 | Software Engineering | 3-0-0-3 | CS202 |
| 3 | CS303 | Machine Learning | 3-0-0-3 | CS206, CS201 |
| 3 | CS304 | Cryptography and Network Security | 3-0-0-3 | CS204 |
| 3 | CS305 | Data Mining and Analytics | 3-0-0-3 | CS206, CS201 |
| 3 | CS306 | Computer Graphics | 3-0-0-3 | CS106 |
| 3 | CS307 | Operating Systems Lab | 0-0-2-1 | CS301 |
| 3 | CS308 | Software Engineering Lab | 0-0-2-1 | CS302 |
| 4 | CS401 | Cloud Computing | 3-0-0-3 | CS204 |
| 4 | CS402 | Big Data Technologies | 3-0-0-3 | CS201, CS305 |
| 4 | CS403 | Artificial Intelligence | 3-0-0-3 | CS303 |
| 4 | CS404 | Internet of Things (IoT) | 3-0-0-3 | CS204 |
| 4 | CS405 | Human-Computer Interaction | 3-0-0-3 | CS106 |
| 4 | CS406 | DevOps and CI/CD | 3-0-0-3 | CS302 |
| 4 | CS407 | Cloud Computing Lab | 0-0-2-1 | CS401 |
| 4 | CS408 | AI and ML Lab | 0-0-2-1 | CS303 |
| 5 | CS501 | Advanced Algorithms | 3-0-0-3 | CS106, CS206 |
| 5 | CS502 | Research Methodology | 3-0-0-3 | - |
| 5 | CS503 | Special Topics in Computer Applications | 3-0-0-3 | - |
| 5 | CS504 | Mobile Application Development | 3-0-0-3 | CS205 |
| 5 | CS505 | Blockchain Technologies | 3-0-0-3 | - |
| 5 | CS506 | Game Development | 3-0-0-3 | CS306 |
| 5 | CS507 | Mobile App Development Lab | 0-0-2-1 | CS504 |
| 5 | CS508 | Blockchain Lab | 0-0-2-1 | CS505 |
| 6 | CS601 | Capstone Project I | 3-0-0-3 | - |
| 6 | CS602 | Advanced Data Science | 3-0-0-3 | CS305 |
| 6 | CS603 | Quantitative Finance | 3-0-0-3 | CS206 |
| 6 | CS604 | Research Ethics and Standards | 3-0-0-3 | - |
| 6 | CS605 | Entrepreneurship in Tech | 3-0-0-3 | - |
| 6 | CS606 | Internship | 0-0-0-12 | - |
| 6 | CS607 | Capstone Project Lab I | 0-0-2-3 | CS601 |
| 6 | CS608 | Research Workshop | 0-0-0-3 | - |
| 7 | CS701 | Capstone Project II | 3-0-0-3 | - |
| 7 | CS702 | Advanced Cybersecurity | 3-0-0-3 | CS304 |
| 7 | CS703 | AI in Industry Applications | 3-0-0-3 | CS303 |
| 7 | CS704 | Distributed Systems | 3-0-0-3 | CS204, CS301 |
| 7 | CS705 | Human-Centered Design | 3-0-0-3 | CS505 |
| 7 | CS706 | Capstone Project Lab II | 0-0-2-3 | CS701 |
| 7 | CS707 | Industry Mentorship Program | 0-0-0-3 | - |
| 7 | CS708 | Final Presentation and Evaluation | 0-0-0-3 | - |
| 8 | CS801 | Specialized Elective Course I | 3-0-0-3 | - |
| 8 | CS802 | Specialized Elective Course II | 3-0-0-3 | - |
| 8 | CS803 | Specialized Elective Course III | 3-0-0-3 | - |
| 8 | CS804 | Specialized Elective Course IV | 3-0-0-3 | - |
| 8 | CS805 | Capstone Thesis and Publication | 0-0-0-6 | - |
| 8 | CS806 | Final Evaluation and Defense | 0-0-0-3 | - |
| 8 | CS807 | Internship Completion Report | 0-0-0-3 | - |
| 8 | CS808 | Graduation Ceremony and Alumni Networking | 0-0-0-1 | - |
The department offers several advanced elective courses that allow students to specialize in specific domains. Here are descriptions of some key departmental electives:
This course introduces students to the fundamentals of machine learning, including supervised and unsupervised learning algorithms, neural networks, deep learning frameworks, and reinforcement learning techniques. Students will gain hands-on experience with libraries like TensorFlow, PyTorch, and Scikit-learn while working on real-world datasets.
This course explores the principles of modern cryptographic systems and network security protocols. Topics include symmetric and asymmetric encryption, hash functions, digital signatures, key management, secure communication protocols, and penetration testing methods. Students will implement security solutions using tools like OpenSSL and Wireshark.
Students learn advanced data mining techniques, including clustering, classification, association rule mining, and anomaly detection. The course covers statistical analysis, predictive modeling, big data technologies like Hadoop and Spark, and data visualization using tools such as Tableau and Power BI.
This course provides an in-depth exploration of computer graphics concepts, including 2D and 3D transformations, rendering techniques, lighting models, texture mapping, and animation principles. Students will develop interactive graphics applications using OpenGL and DirectX APIs.
The course covers cloud computing architectures, service models (IaaS, PaaS, SaaS), deployment models, virtualization technologies, containerization with Docker and Kubernetes, and cloud security practices. Students will gain experience with major cloud platforms like AWS, Azure, and Google Cloud.
This course introduces students to big data processing frameworks such as Hadoop, Spark, Kafka, and NoSQL databases. Students will learn how to process and analyze large datasets using distributed computing techniques and gain insights into scalable data architectures.
The course explores the core concepts of artificial intelligence, including knowledge representation, search algorithms, planning, decision-making under uncertainty, natural language processing, computer vision, robotics, and ethical AI practices. Students will build intelligent agents using Python-based libraries like NLTK and OpenCV.
This course examines the architecture and implementation of IoT systems, including sensor networks, embedded systems, wireless communication protocols, edge computing, and data analytics for smart environments. Students will develop IoT applications using platforms like Arduino, Raspberry Pi, and ESP32.
The course focuses on designing user-friendly interfaces and interactive systems. It covers usability principles, cognitive psychology, interaction design patterns, prototyping tools, accessibility standards, and user experience evaluation methods. Students will conduct usability studies and develop prototype interfaces.
This course teaches students about DevOps practices and continuous integration/continuous deployment pipelines. It includes automation tools like Jenkins, GitLab CI, Docker, Kubernetes, Ansible, and monitoring systems. Students will implement end-to-end CI/CD workflows in cloud environments.
This course provides a comprehensive overview of mobile app development for both iOS and Android platforms. Students will learn about UI design principles, platform-specific APIs, mobile databases, networking, and security best practices. The course includes hands-on labs using Xcode and Android Studio.
The course covers blockchain fundamentals, consensus mechanisms, smart contracts, decentralized applications (dApps), cryptocurrency frameworks, and enterprise blockchain solutions. Students will build and deploy blockchain applications using Ethereum, Hyperledger Fabric, and Solidity.
This course introduces students to game development principles using industry-standard engines like Unity and Unreal Engine. Topics include game design patterns, physics simulation, scripting languages, asset creation, and multiplayer networking. Students will develop complete games from concept to release.
The department emphasizes project-based learning as a cornerstone of its educational philosophy. This approach ensures that students not only understand theoretical concepts but also apply them in real-world scenarios.
Mini-projects are integrated throughout the curriculum, beginning in the first year and escalating in complexity over time. These projects typically involve small teams of 3-5 students working under faculty supervision on topics aligned with current industry trends or academic research interests.
The final-year thesis/capstone project is a significant component of the program. Students are expected to choose a topic relevant to their specialization, conduct in-depth research, and deliver a comprehensive report and presentation. The projects often involve collaboration with industry partners, leading to potential publications or patent applications.
Faculty members play a crucial role in guiding students through the project selection process. They help identify relevant research areas, suggest suitable methodologies, and provide mentorship throughout the development phase. Regular feedback sessions and milestone reviews ensure that projects stay on track and meet academic standards.
