1. AI & Cognitive Computing Lab

The AI & Cognitive Computing Lab focuses on developing intelligent systems that can learn, reason, and make decisions. Students explore areas such as machine learning, deep learning, natural language processing, and computer vision to build smart applications that solve real-world problems. The lab utilises advanced tools such as Python, JupyterLab, NumPy, Pandas, Scikit-learn, TensorFlow / PyTorch, OpenCV, and MLflow to support data analysis, machine learning, and deep learning development.

2. Cloud Infrastructure & DevOps Lab

The Cloud Infrastructure & DevOps Lab provides hands-on experience in designing, deploying, and managing scalable cloud-based applications. It enables students to work with cloud platforms, virtualisation, containerization, CI/CD pipelines, and automation tools to understand modern cloud computing and DevOps practices. The lab utilises leading Cloud platforms such as Amazon Web Services, VMware, Microsoft Azure, and IBM Cloud to provide hands-on experience in cloud infrastructure and DevOps Lab.

3. Cyber Security & Digital Forensics Lab

The Cyber Security & Digital Forensics Lab is dedicated to studying cyber threats, secure system design, and digital investigation techniques. Students gain practical exposure to ethical hacking, network security, malware analysis, incident response, and forensic analysis to protect digital systems and investigate cybercrimes. The lab uses industry-standard cybersecurity tools such as Kali Linux, Wireshark, Metasploit Framework, and Burp Suite to provide hands-on training in ethical hacking and digital security.

4. Robotics & Automation Lab

The Robotics & Automation Lab provides a platform for designing and building intelligent robotic systems. The Robotics & Intelligence Lab utilises hardware such as robotic kits, microcontrollers, sensors, actuators, and embedded development boards to design and build intelligent robotic systems. Software tools like MATLAB, ROS, Python, and Arduino IDE are used for robot programming, simulation, control systems, and AI-based automation applications.

5. Immersive Reality Lab

The Immersive Reality Lab explores emerging technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). Students create interactive simulations and immersive applications for education, gaming, healthcare, and industrial training. The Immersive Reality Lab uses advanced development platforms such as Unity, Unreal Engine, Blender, and Vuforia to create interactive virtual and augmented reality experiences. These tools enable students to design immersive simulations, 3D environments, and AR/VR applications for gaming, education, healthcare, and industrial training.

6. Full Stack Development Lab

The Full Stack Development Lab enables students to build complete web applications from front-end interfaces to back-end services and databases. The lab focuses on modern web technologies, frameworks, APIs, and deployment practices to develop scalable and user-friendly applications. The lab utilises leading Cloud platforms such as Snowflake, Databricks, and Amazon Redshift to provide hands-on experience in full-stack web development.

7. Data Engineering & Data Science Lab

The Data Engineering & Data Science Lab focuses on extracting insights from large datasets through data processing, analytics, and machine learning. Students work on data pipelines, big data technologies, statistical modeling, and predictive analytics to support data-driven decision making. The lab utilizes leading cloud infrastructure platforms such as MATLAB, IBM SPSS, SAS, Tableau, Rapid Miner to provide hands-on experience in cloud infrastructure.

8. Semiconductor & Physical Computing Lab

The Semiconductor & Physical Computing Lab provides practical exposure to electronics, microcontrollers, and hardware programming. Students work with sensors, embedded systems, IoT devices, and semiconductor technologies to build smart hardware solutions and prototype physical computing applications. The Semiconductor & Physical Computing Lab uses development tools such as Arduino IDE, MATLAB, Proteus, and Keil µVision for designing and testing embedded and semiconductor-based systems.