Dept. of Computer Application
| MCA Students | |
|---|---|
| Research Scholars | 05 |
| Publications |
| Faculty | 0 |
|---|---|
| Staff | 0 |
Laboratories
The Department has a very rich heritage when it comes to computing facilities made available to students. The department famously housed a PDP-11 machine, the first of its kind to be hosted in any technical institute, from 1982 to 2015 when it was decommissioned. Regular upgrades are made to all systems in the laboratory to ensure smooth conduct of lab session and research activities. Today, the department has some of the finest computing hardware in the institution with a mix of high end and mid tier machines that are used for research and for academic work. The department was recently sanctioned a research lab to be used exclusively for final year project and other research works with 56 laptop machines along with high speed internet connectivity and smart classroom capabilities. The students of the department are also given access to central computing facility of the college for general use.
Faculty and staff in charge : Dr. Nadera Beevi S & Mr.Basith Nazar
Suggested Laptop Specifications for MCA Students
To effectively handle coursework and projects, especially those involving machine learning,
development environments, and advanced programming, we recommend that students use laptops
meeting certain performance standards. The suggested minimum system specification guidelines for
MCA students outline practical and up-to-date requirements, aligned with 2025 expectations for a
professional computing lab focused on development and machine learning (ML) workloads.
We suggest that MCA students ensure their laptops meet the following specification:
| Component | Minimum Specification | Preferred Specification | Notes |
|---|---|---|---|
| Processor (CPU) | Intel Core i5 12th/13th Gen (H/HX) AMD Ryzen 5 7000 (H/HS/HX) |
Intel Core i7 14th Gen (H/HX) AMD Ryzen 7 8000 (H/HS/HX) |
At least 6 cores, ideal for multitasking & ML workloads |
| RAM | 16 GB DDR4 | 16 GB DDR5 (expandable) | Required for IDEs, Docker, ML frameworks |
| Storage | 512 GB NVMe SSD | 1 TB NVMe SSD or higher | Fast boot, more space for datasets |
| Graphics (GPU) | NVIDIA RTX 3050 AMD Radeon RX 6600M |
NVIDIA RTX 4050 or higher | Dedicated GPU is critical for ML/AI frameworks |
| Display | 15.6" Full HD, IPS | 15.6" Full HD, IPS, high refresh rate | IPS for color accuracy, avoid TN panels |
| Battery Life | 6 hours real usage | 8+ hours real usage | For long academic sessions |
| Ports | USB 3.2, USB-C, HDMI, Ethernet | Thunderbolt 4, multiple USB-C/HDMI | Ensure compatibility with peripherals |
| Operating System | Windows 11 (mandatory) | Windows 11 & Linux dual boot | Linux recommended for ML & dev tools |
• Enables efficient machine learning and software development workflows.
• Ensures compatibility with latest IDEs, Docker, and ML frameworks (like TensorFlow, PyTorch).
• Future-proofs student investment for the length of the MCA programme.
Note: Meeting these specifications ensures smooth participation in coursework, programming, and machine learning projects. Lower configurations can lead to performance challenges in real-world academic use.