Admission 2026

Computer Science with AI & ML

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Infrastructure and Facilities

The Department of Computer Science & Engineering (Artificial Intelligence and Machine Learning) and Master of Computer Applications is supported by a computing ecosystem designed for high-performance data processing, algorithm development, deep neural network training, and enterprise application engineering.

Our laboratory infrastructure provides high-speed networked computing systems, dedicated GPU acceleration, open-source AI frameworks, and industry-standard development suites to ensure students gain practical, end-to-end software and model engineering experience.

Specialized Laboratory Facilities

Laboratory Name System Configuration & Hardware Software & Tools Installed Courses / Practical Focus Supported
John McCarthy Intelligence & Machine Learning Lab Intel Core i5-10400 / High-Performance systems, 16GB+ RAM, High-Speed GigE Network Python, NumPy, SciPy, Pandas, Scikit-Learn, TensorFlow, PyTorch, JupyterLab, Spyder, R-Lang, MongoDB, XAMPP Foundations of Machine Learning, Deep Learning, Data Analytics, Python for AI, NLP & Computer Vision
Ada Lovelace Project & Research Lab High-end Core i3/i5 multi-core workstations, dedicated research terminals Visual Studio, Eclipse, Java, Dev-C++, Python, K7 Security Suite, Linux/Windows OS Mini Projects, AI Innovation & Product Development (IPD), Open-Source Projects, Research Development
Bill Gates Enterprise & Database Systems Lab Multi-terminal systems with dual-boot Windows / Fedora Linux environments Oracle, MySQL, MS Access, Apache Hadoop, Android Studio, Eclipse, Dev-C++, Java Database Management Systems (DBMS), Operating Systems, Mobile Application Development, Big Data Analytics
Narayanamurthy Software Programming Lab Systems equipped with multi-core processors, high-speed campus LAN connectivity Java SDK, Dev-C++, Eclipse, NetBeans, Visual Studio, Rational Rose (UML tools) Object-Oriented Programming (Java/C++), Data Structures & Algorithms, Object-Oriented Analysis and Design (OOAD)
Alan Turing Postgraduate & Advanced Computing Lab Dedicated PG workstations with i3/i5 processing nodes and simulation testbeds NS2/NS3, OPNET, Eclipse, Oracle, Java/Python, Enterprise Web Frameworks MCA Advanced Data Structures Lab, Full-Stack Web Development, MCA Capstone Projects

Computing & Network Infrastructure

  • Hardware & Compute Power: Workstations with multi-core Intel i5/i3 architectures and dedicated graphics cards for running matrix computations, deep learning models, and local virtual machines.
  • Network Backbone: Dedicated high-speed campus-wide LAN and high-bandwidth Wi-Fi for uninterrupted access to cloud instances, GitHub repositories, and dataset downloads.
  • Operating Systems & Environments: Dual-boot flexibility supporting Windows 10/11 and Fedora/Ubuntu Linux across programming terminals.
  • Power Continuity: Centralized Online UPS backup system ensuring continuous operation during lab practicals, assessments, and computational model runs.