About the Department

The Department of Computer Science and Engineering was established in 2007 and offers an undergraduate program identified as B.Tech in CSE. Initially, the department admitted 60 students, but this number was later raised to 90 in 2009, 180 in 2012, 360 in 2023, and 420 in 2024. The UG-CSE program is accredited by NBA in 2016, 2019, and 2022, and it is valid until 30 June 2025.

Faculty members of the department are extremely knowledgeable and talented. They impart their expertise in a variety of UG program courses because of their varied backgrounds in computer science and engineering. In order to enhance students’ practical skills, the department keeps firm relationships with numerous industries.

MOUs are inked with industries in Hyderabad, Bangalore, and Chennai to foster industry-institution interaction. Through this contact, staffs and students participate in real-world initiatives, plan industrial trips, and receive training and internship possibilities. The students’ success rate has above 90% throughout the past three years.

Laboratories are spacious and well-equipped with advanced configuration technologies. The ratio of students to computers is maintained at 1:4. New experiments are conducted in each lab to provide the students great and impactful practical experience.

Welcome to the Department of Computer Science and Engineering at St. Peter’s Engineering College.

Our department is committed to providing an exceptional learning environment where students are empowered to become Future-ready technologists, Innovators, and Problem solvers. With a curriculum that balances foundational knowledge and Emerging Technologies, we focus on areas like Artificial Intelligence, Machine Learning, Cybersecurity, Data Science, Cloud Computing, and Software Engineering.

Our dedicated Faculty members guide students not just in academics but also in Research, Innovation, and Entrepreneurship. We strongly encourage student participation in Hackathons, Coding Competitions, Internships, and Industry Projects to prepare them for real-world challenges.

We are proud of our vibrant student community, dynamic research initiatives, and strong placement records. We invite you to be part of this exciting journey and contribute to shaping the future of technology.

Head of Department

Dr. Amjan Shaik

Email: [email protected]

Phone: 9866040342

Vision

To be a global leader in Computer Science Education, Research and Development, Innovation through industry collaboration and cultivating future-ready technologists.

Mission

DM 1: Cultivate experiential learning through state-of-the-art technologies and algorithms to address real-world interdisciplinary challenges.

DM 2: Collaborate with industry and academia to equip students with cutting-edge skills and prepare them for dynamic careers.

DM 3: Strengthen theoretical and applied research in Computer Science & Engineering, fostering innovation, impactful contributions, and instilling ethical values and social responsibility in all endeavors.

Program Educational Objectives

PEO 1: Innovate and contribute to research, driving technological advancements in industry and society.

PEO 2: Excel as leaders in software development, ensuring industry and government excellence.

PEO 3: Lead entrepreneurial ventures, fostering growth in computer science-driven technologies at national and global levels.

Program Outcomes

PO: 1 ENGINEERING KNOWLEDGE: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO: 2 PROBLEM ANALYSIS: Identity, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using the first principles of mathematics, natural sciences, and engineering sciences.

PO: 3 DESIGN/DEVELOPMENT OF SOLUTIONS: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for public health and safety, and cultural, societal, and environmental considerations.

PO: 4 CONDUCT INVESTIGATIONS OF COMPLEX PROBLEMS: Use research-based knowledge and research methods including design of experiments, analysis, and interpretation of data, and synthesis of the information to provide valid conclusions.

PO: 5 MODERN TOOL USAGE: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.

PO: 6 THE ENGINEER AND SOCIETY: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

PO: 7 ENVIRONMENT AND SUSTAINABILITY: Understand the impact of professional engineering solutions in societal and environmental contexts, demonstrate the knowledge of, and need for sustainable development.

PO: 8 ETHICS: Apply ethical principles and commit to professional ethics, responsibilities, and norms of the engineering practice.

PO: 9 INDIVIDUAL AND TEAM WORK: Function effectively as an individual, and as a member or leader in diverse teams, and multidisciplinary settings.

PO: 10 COMMUNICATION: Communicate effectively on complex engineering activities with the engineering community and with society, such as being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

PO: 11 PROJECT MANAGEMENT AND FINANCE: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

PO: 12 LIFE-LONG LEARNING: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Program Specific Outcomes

PSO-1 Design and develop computing subsystems for data storage, communication, information processing, and knowledge discovery.

PSO-2 Design algorithms for real-world problems, focusing on execution and complexity analysis while considering security, cost, quality, and privacy parameters in software development.

Under Graduate Program

NBA Accreditation of Computer Science and Engineering
B.Tech Program

The details of the NBA accreditation status and the programs accredited are as follows:

CO - PO / PSO Mapping and Justification

Program Curriculum

Faculty Profiles

Laboratories

Programming for Met cognitive Lab(S47)

The Programming for Metacognitive Laboratory is aimed at enhancing students' problem-solving capabilities through metacognitive strategies, emphasizing the awareness and regulation of their thinking during programming tasks. This lab encourages students to reflect on their coding approaches, identify errors, and develop self-regulation techniques while implementing logical solutions. Through guided exercises, algorithm tracing, and code debugging sessions, students explore various ways to optimize code efficiency and improve comprehension. This lab helps foster cognitive awareness, critical thinking, and reflective learning, preparing students to become thoughtful and effective problem solvers.

Experiments

Data Structures Lab(S48)

The Data Structures Laboratory is structured to provide students with hands-on experience in designing, implementing, and analyzing data structures that are fundamental to computer science. This lab complements theoretical concepts such as arrays, linked lists, stacks, queues, trees, graphs, and hashing by offering real-world programming exercises. Students learn to write efficient and optimized code using sorting, searching, and traversal algorithms. By engaging in implementation-based tasks and performance comparisons, the lab helps develop analytical thinking, coding precision, and foundational skills necessary for advanced programming and algorithm development.

Experiments

Fundamentals of Python Programming Lab(S11)

The Fundamentals of Python Programming Laboratory introduces students to the basics of programming using Python, a versatile and widely-used language in modern software development and data science. This lab provides a practical environment to understand variables, control structures, functions, object-oriented programming, and file handling. With its emphasis on clean and readable code, Python allows students to focus more on problem-solving than syntax. The lab fosters creativity, logical reasoning, and confidence in programming, laying a strong foundation for further coursework in data analytics, machine learning, and web development.

Experiments

Database Management systems Lab(S11A)

The Database Management Systems Laboratory offers a practical understanding of database concepts, focusing on the design, creation, and manipulation of relational databases. Students gain hands-on experience using SQL and PL/SQL to perform operations such as data definition, querying, joins, indexing, and transactions. The lab also introduces students to normalization techniques, ER modeling, and stored procedures. Through the use of database management tools like MySQL or Oracle, the lab bridges theory and practice, enabling students to design robust and efficient database systems for real-world applications.

Experiments

Operating Systems Lab(F20)

The Operating Systems Laboratory is designed to provide students with practical exposure to the core concepts of operating systems, which are central to modern computing. Through hands-on experiments, students explore process management, memory allocation, file systems, CPU scheduling algorithms, and synchronization techniques. Using C and Linux-based environments, they implement various OS modules and simulate real-time scenarios such as deadlock handling and inter-process communication. This lab reinforces theoretical learning, fosters system-level thinking, and equips students with the skills to design efficient and reliable operating systems components.

Experiments

Computer Networks Lab(F17)

The Computer Networks Laboratory provides a platform for students to understand and implement networking protocols, data communication techniques, and socket programming. Through practical exercises, students configure network topologies, simulate data transfer using TCP/IP and UDP, and analyze network traffic using tools like Wireshark. The lab also includes routing and switching experiments using Packet Tracer and real-time networking hardware. This hands-on environment helps students gain a deep understanding of how networks operate, while enhancing their diagnostic and troubleshooting abilities in network configurations.

Experiments

Object Oriented programming through JAVA Lab(S13)

The Object-Oriented Programming through Java Laboratory introduces students to the principles of object-oriented programming and software design using Java. Students work on creating classes and objects, applying concepts such as inheritance, polymorphism, abstraction, and encapsulation. The lab also involves exception handling, file I/O operations, and GUI application development using Java Swing. Through structured programming tasks and problem-solving activities, students develop modular and reusable code, preparing them for larger software development projects and real-world application building.

Experiments

Software Engineering Lab(F14)

The Software Engineering Laboratory is focused on providing students with practical exposure to the software development life cycle (SDLC), including planning, analysis, design, development, testing, and documentation. Students engage in team-based projects that follow engineering principles, utilizing tools for creating UML diagrams, generating software requirement specifications, and managing project timelines. This lab emphasizes collaboration, version control, and quality assurance practices, thereby preparing students for professional software engineering roles and industry-standard development environments.

Experiments

WAD & NLP Lab(S17)

The Web Application Development & Natural Language Processing Laboratory offers a dual-focus platform where students learn to build dynamic, responsive web applications while also exploring foundational NLP techniques. In the web development component, students use HTML, CSS, JavaScript, and server-side scripting languages such as PHP or Python (Flask/Django). The NLP segment introduces students to text processing, tokenization, stemming, and sentiment analysis using libraries like NLTK and spaCy. This lab equips students with cross-disciplinary skills needed for developing intelligent web interfaces and language-based applications.

Experiments

Internet of Things Lab(G11)

The Internet of Things (IoT) Laboratory provides students with experiential learning in designing, building, and deploying IoT-enabled systems. Students use microcontrollers such as Arduino and Raspberry Pi to interface with various sensors and actuators, and implement real-time data collection and communication. Experiments include temperature monitoring, motion detection, and smart automation using Wi-Fi and Bluetooth modules. Cloud integration through platforms like ThingSpeak or Blynk is also explored. This lab nurtures innovation, hands-on circuit design, and the integration of software and hardware components for smart applications.

Experiments

Automata and Compiler Design Lab(S20)

The Automata and Compiler Design Laboratory introduces students to the practical aspects of language theory and compiler construction. Students perform experiments involving lexical analysis, syntax parsing, and finite automata simulation using tools like LEX, YACC, and JFLAP. They implement modules for token generation, grammar parsing, and syntax-directed translation. The lab bridges theoretical concepts in formal languages with hands-on applications in compiler design, preparing students to understand language processors and the internal workings of programming language translation.

Experiments

Data Mining Lab(S21)

The Data Mining Laboratory focuses on the extraction of useful patterns and knowledge from large datasets. Students engage in data preprocessing, transformation, and visualization, and perform classification, clustering, and association rule mining using tools such as Weka, R, or Python (scikit-learn, pandas). Through practical datasets and use-case simulations, the lab emphasizes real-world applications in business intelligence, healthcare, and social data analytics. It enhances analytical thinking and prepares students for careers in data science and big data technologies.

Experiments

FML & NLP Lab(S8)

The Formal Methods and Natural Language Processing Laboratory provides a unique blend of theoretical computing and AI-based language processing. The FML component introduces students to mathematical models, propositional logic, and model checking, while the NLP section focuses on language processing tasks such as POS tagging, parsing, and named entity recognition. Tools and languages like Prolog, Python (with NLTK/spaCy), and symbolic logic simulators are used. This integrated lab fosters logical reasoning, linguistic computing, and prepares students for research and development in AI, linguistics, and formal software verification.

Experiments

E-Resources

Projects

R & D Activities

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