CSE AIML Laboratories
Laboratories
The Department of Computer Science and Engineering (AI & ML) is equipped with advanced and industry-aligned laboratories that provide students with hands-on experience, practical skill development, and exposure to real-time software and hardware environments.Each lab is designed to support project-based learning, experimentation, and research in core and emerging areas of computing and artificial intelligence.
The department hosts the following laboratories:
Skill Development Lab(NodeJS/ReactJS/Django) Lab
The Full Stack Web Development Lab provides hands-on training in modern web technologies, covering frontend design, backend development, database connectivity, REST APIs, authentication, and deployment practices. Students develop responsive and interactive web applications using HTML5, CSS3, JavaScript, Bootstrap, React, Node.js, Express, Servlets, and databases like MySQL/Oracle. The lab emphasizes real-world application development, session management, API integration, and deployment workflows, enabling students to build scalable full-stack applications for industry-oriented use cases.
AR VR Lab
The AR/VR and Game Development Lab provides hands-on training in interactive game design, 3D environment creation, virtual reality, and augmented reality application development using Unity and C#. Students learn to design immersive 2D/3D experiences by implementing game physics, animations, UI systems, player interactions, AI-based enemy behavior, and scoring mechanisms. The lab also introduces AR and VR technologies using tools such as Oculus and Vuforia, enabling students to develop and deploy real-time immersive applications for gaming, simulation, education, and industrial use cases.
Operating Systems Lab
The Operating Systems Lab provides practical exposure to core operating system concepts such as process scheduling, memory management, deadlock avoidance, inter-process communication, synchronization, and file system operations using C programming in UNIX/Linux environments. Students implement CPU scheduling algorithms, semaphores, paging, segmentation, page replacement policies, and IPC mechanisms like pipes, FIFOs, message queues, and shared memory. The lab emphasizes system-level programming using UNIX/Linux system calls, enabling students to understand resource management, concurrency control, and process coordination in modern operating systems.
Software Engineering Lab
The Software Engineering Lab provides practical training in software development life cycle activities including requirement analysis, system design, software testing, risk management, and configuration management. Students learn to prepare Software Requirement Specification (SRS) documents, design documents, testing reports, and project management artifacts while applying software engineering principles to real-world applications. The lab also introduces CASE tools for system modeling and design, along with white-box and black-box testing techniques for quality assurance. Through mini-projects and open-ended experiments, students gain hands-on experience in building scalable software systems, understanding architectural trade-offs, authentication mechanisms, API integration, and performance optimization practices.
Database Management Systems Lab
The Database Management Systems Lab provides hands-on training in database design, development, and management using relational database concepts and SQL programming. Students learn to design databases using E-R models, convert them into relational schemas, and apply normalization techniques to ensure efficient data organization. The lab covers DDL, DML, complex SQL queries, joins, subqueries, aggregate functions, views, triggers, procedures, and cursors for effective database operations and automation. Through real-world applications such as banking, hospital, and employee management systems, students gain practical experience in data storage, retrieval, analysis, and database administration for enterprise-level applications.
DevOps Lab
The DevOps Lab provides practical exposure to software development automation, version control, continuous integration, containerization, orchestration, and automated testing using tools such as Git, GitHub, Jenkins, Docker, Kubernetes, Selenium, Helm, and Docker Compose. Students learn to develop, test, deploy, and manage scalable multi-service applications using modern DevOps and CI/CD practices.
Machine Learning Lab
The Machine Learning Lab provides hands-on experience in statistical analysis, data visualization, and machine learning using Python libraries such as NumPy, Pandas, Matplotlib, SciPy, and Scikit-Learn. Students implement algorithms like Linear Regression, Decision Trees, KNN, Logistic Regression, SVM, K-Means Clustering, HMM, and LDA for real-world prediction, classification, and clustering applications.
