Computer Science & Engineering
Overview of Computer Science & Engineering Department
The department of Computer Science and Engineering was started in the year 2010 with an intake of 60 students. Later on, the intake was increased to 180 students in the year 2024.The department is headed by Dr. SreeRama Reddy who has more than twenty years of experience in teaching in reputed engineering college.
The department is well equipped with a fully centralized air-conditioned computer centre with LAN connection. The department has well qualified, experienced and dedicated faculty members specialized in object-oriented system analysis and design, artificial intelligence, expert systems, distributed computing, multimedia, RDBMS, computer networks, neural networks, data communication, OOPS, data structures and algorithms, software engineering, operating system and network security.
The students of this course develop base skills in programming, design of algorithms, software development cycle, operating system software, kernel programming and project management. In order to imbibe these skills, the department possesses different laboratories which are equipped with latest technologies as prescribed by the university. In addition to the regular classroom teaching, the students are exposed to additional skills by giving them an opportunity to visit industries, participate in guest lecturers etc. In addition, the department provides placement opportunities by inviting different software companies to the institution and providing technical hands on training to the students.
Department thrive to widen the awareness of students in professional, ethical, social and environmental dimensions, to strengthen the theoretical and practical aspects of the learning process, to ensure students acquire unique skills to design and develop and to find solutions of the highest quality and standards to resolve software problems and issues while maintaining the academic results not to fall below 95%.
Department Logo of CSE
Vision
To impart the best in academia that empowers the students of Computer Science and Engineering to contribute their best for the society.
Mission
To mold the students as responsible professionals and citizens by providing an excellent learning environment
To equip the students with wisdom- theory and practical in the discipline of computing and the ability to apply knowledge to the benefits of the society
Laboratory
Programming Laboratory
A Programming Laboratory is a dedicated space equipped with computers and software for students to practice coding. It provides hands-on experience, fostering understanding of programming concepts and languages through practical application. Labs often offer support from instructors or assistants to aid learners in their coding endeavors.
Software Used:
C & C++ Language (Windows)
Data Structure Laboratory
A Data Structure Laboratory is a specialized facility where students experiment with organizing and manipulating data efficiently. It offers hands-on practice in implementing and analyzing various data structures like arrays, linked lists, trees, and graphs. This experiential learning enhances comprehension and problem-solving skills in managing complex data arrangements.
Software Used:
C++ Language (Windows / Ubuntu)
Database Management System Laboratory
A Database Management System Laboratory is a dedicated space for students to learn and practice managing databases. It provides hands-on experience in designing, querying, and maintaining databases using software like SQL. This practical setting allows learners to understand database concepts and gain proficiency in handling real-world data storage and retrieval tasks.
Software Used:
MySQL, Oracle (Windows)
Operating System Laboratory
An Operating System Laboratory is a specialized environment where students explore the principles and functionality of operating systems. Through hands-on exercises, they gain practical experience in tasks like process management, memory allocation, file systems, and networking. This immersive learning enhances comprehension of how operating systems facilitate computer functionality and resource management.
Software Used:
C Language, Windows and Ubuntu Terminal.
Data Science Laboratory
A Data Science Laboratory is a dedicated space where students gain hands-on experience in applying statistical, mathematical, and computational techniques to analyze and interpret complex data sets. Through practical exercises, learners develop skills in data visualization, machine learning, and data mining, preparing them for real-world data-driven problem-solving tasks.
Software Used:
Python and R Programming Language
Design and Analysis of Algorithms Laboratory
The Design and Analysis of Algorithms focuses on developing efficient solutions to computational problems. Students study algorithmic design paradigms, analyze their correctness and complexity, and evaluate their performance. Through theoretical study and practical implementation, learners gain expertise in solving diverse computational challenges, preparing them for advanced problem-solving in computer science.
Software Used:
C Language Windows Terminal
Data Analytics with Excel Laboratory
In a Data Analytics with Excel Laboratory, students engage in practical exercises to analyze data using Excel’s functions and features. Through hands-on exploration, they learn to manipulate, visualize, and interpret datasets, acquiring skills in data cleansing, pivot tables, statistical analysis, and visualization techniques, preparing them for data-driven decision-making roles.
Software Used:
Microsoft Excel
Machine Learning Laboratory
In a Machine Learning Laboratory, students delve into hands-on experimentation with algorithms and models to analyze and predict patterns in data. Through practical exercises, they gain proficiency in tasks like data preprocessing, model training, evaluation, and optimization, preparing them for real-world applications in various fields reliant on machine learning techniques.
Software Used:
Python Language
Python Programming Laboratory
The Python Programming Laboratory provides hands-on experience in Python language essentials, data structures, algorithms, and problem-solving techniques. Through practical exercises and projects, students develop proficiency in coding, debugging, and software development, fostering a strong foundation for programming in various domains.
Software Used:
PyCharm and Python Language
Object Oriented with Java Laboratory
The Object Oriented with Java Laboratory immerses students in Java programming, emphasizing object-oriented principles such as inheritance, encapsulation, and polymorphism. Through hands-on exercises and projects, learners develop proficiency in designing and implementing Java applications, gaining essential skills for building robust and scalable software solutions.
Software Used:
C++ Language
R Programming Lab
The R Programming lab provides hands-on experience in statistical computing and data analysis using the R programming language. Students learn to manipulate data, create visualizations, and perform statistical tests. Practical exercises reinforce concepts such as data cleaning, exploration, and modeling, preparing students for real-world analytical tasks in various fields.
Software Used:
R Studio
Digital Image Processing Laboratory
The Digital Image Processing Laboratory delves into the theory and application of techniques for manipulating and analyzing digital images. Students explore methods such as filtering, segmentation, and feature extraction through hands-on projects. This laboratory equips learners with skills vital for image enhancement, recognition, and computer vision applications.
Software Used:
Photoshop and Lightroom
Mobile Application Development Laboratory
The Mobile Application Development Laboratory focuses on creating applications for mobile platforms like iOS and Android. Students learn about UI/UX design, programming languages (e.g., Swift, Java, Kotlin), and integrating features such as GPS, sensors, and databases. Through hands-on projects, learners gain proficiency in building functional and user-friendly mobile apps.
Software Used:
XCode
Microcontroller and Embedded Systems Laboratory
Course Learning Objectives and Outcomes:
- Develop and test Program using ARM7TDMI/LPC2148
- Conduct the experiments on an ARM7TDMI/LPC2148 evaluation board using evaluation versionof Embedded ‘C’ & Keil Uvision-4 tool/compiler.
Software/Applications Used: Micro Vision/ Keil Uvision-4 and Flash Magic
Value Added Course
A Value-Added Course for CSE (Computer Science & Engineering), these courses will enhance and complement their core curriculum and enhance their skill set. Here are some suggestions:
Data Structures and Algorithms: This course is fundamental for any CSE student. It teaches efficient ways to organize and manipulate data, which is crucial for developing efficient software and algorithms.
Machine Learning and Artificial Intelligence: With the rise of AI and machine learning applications in various industries, having knowledge in this field can greatly boost your career prospects. Understanding algorithms, data preprocessing, and model evaluation are key components.
Cyber Security: As technology advances, the need for cyber Security experts is growing rapidly. Courses in cyber Security cover topics such as network security, cryptography, ethical hacking, and digital forensics.
Cloud Computing: Cloud computing has become the backbone of many modern applications. Learning about cloud platforms like AWS, Azure, or Google Cloud can be highly beneficial. Understanding concepts like virtualization, containerization, and scalability are crucial.
Mobile App Development: With the increasing use of smartphones, mobile app development skills are in high demand. Courses covering mobile development platforms like Android or iOS, along with languages like Swift or Kotlin, can be very valuable.
Database Management Systems (DBMS): Proficiency in managing and querying databases is essential for many software development roles. Courses covering SQL, NoSQL, database design, and optimization can be highly beneficial.
Software Engineering: Understanding software development methodologies, version control systems like Git, and best practices for software design and testing are crucial for building scalable and maintainable software systems.
Internet of Things (IoT): IoT is revolutionizing various industries by connecting devices and collecting data. Courses covering IoT architecture, protocols, and programming can be valuable for students interested in this field.
Blockchain Technology: Blockchain is gaining popularity beyond cryptocurrencies, with applications in areas like supply chain management, healthcare, and finance. Understanding blockchain concepts and development platforms can be advantageous.
Web Development: Understanding web technologies such as HTML, CSS, JavaScript, and various frameworks like React, Angular, or Vue.js can open up opportunities in web development, which is a continuously growing field.
PROGRAM OUTCOME (POs)
1 Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
2 Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
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 the public health and safety, and the cultural, societal, and environmental considerations.
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.
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.
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.
7 Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
8 Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
9 Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
10 Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
11 Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
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 EDUCATIONAL OBJECTIVES (PEOs)
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PROGRAM SPECIFIC OUTCOMES (PSOs)
To View PEOs and PSOs Details Click Here
COs
