Artificial Intelligence (AI) is not a subject, it’s a revolutionary driving force and it’s restructuring the design of education, the way it’s being delivered, or what students are learning. At NCU in Gurugram, AI is at the centre of the innovation that is occurring in postgraduate studies, such as the M.Tech courses in Data Science and Cybersecurity. NCU forges professionals who are technically competent and yet responsible and ethical, and industry-ready, through AI-enabled learning, smart labs, project-based learning and collaboration with the industry.

1. Adaptive and Personalized Learning for Each Student

AI-powered learning platforms have revolutionized how teaching and learning is done at NCU and this enables individualized pathways. Classroom models may presume equal rates of learning, and AI tools can evaluate a student’s learning pace, or strengths, as well as what they may need more emphasis on.

For Data Science students in M.Tech, AI systems can suggest such things as deep learning modules, or computer vision modules that handle, such as big data analysis from interests and past showings. Students of Cybersecurity can be provided adaptive suggestions regarding penetration test topics, or ethical hacking, including cryptographic protocols.

This adaptive learning approach implies that all students learn at their own pace, receive personalized feedback, or excel in areas they have chosen, so learning becomes actually student-centered, quite beneficial or potent.

2. Intelligent Laboratories for Realistic and Hands-On Learning

Practical work continues to be the foundation for any form of technical education at postgraduate level sometimes it appears. NCU’s AI-powered labs are revolutionizing learning through hands-on training and automating standard steps such as simulations of real-world type scenarios.

Within Data Science labs, the use of AI tools aids students in aspects such as data preprocessing and visualizing and assessing their models in an effective manner. Students can identify quickly the accuracy rates of models, or errors trends overall, along with optimization strategies too, in addition to simply considering accuracy itself. This will boost testing, alongside enhancing understanding.

In Cybersecurity labs, AI presents very realistic simulations and they are live, not stale or repetitive. Students are able to engage with AI opponents which are programmed to be challenging like actual cyber threats rather than predetermined ones. Simulations adapt with a student’s approach to secure data, which can provide learning that has a semblance of real scenarios it turns out. This type of learning prepares the students to handle advanced data or fresh, changing threats in a most effective manner as time continues in reality.

3. Project-Based Learning Powered by Actual Data and Situations

In NCU, M.Tech courses emphasize learning through actual projects such as coding activity or solving other assignments. AI improves this further by including means to utilize larger, real-life sets of data in addition to providing tools to build synthetic data.

For Data Science projects, students work on real challenges they would encounter working in the job market, such as monitoring maintenance so that it will not fail, or fraud detection for financial operations, and performing analysis of health needs as well, creating data which is anonymized by taking away identifiers or making it appear more realistic. And this connects any dividing gaps that exist between education and an industry based learning setup for certain individuals at the current time.

In Cybersecurity, AI generates scenarios such as automated means of discovering security weaknesses or discovering faults as they occur in traffic that passes through a server or it assists in conducting analysis on numerous various malware types, which can include things on varying intelligence levels. Such learning activities construct more knowledge, as well as demanding original thinking while also increasing work independence.

4. Intelligent Evaluation and Ongoing Feedback

AI has transformed how NCU students receive their evaluation and how it is done. AI tools and testing methodologies fuelled by AI can provide a complete analysis to various lines of programming code detecting programming or grammatical glitches, handling also research records in brief.

AI application may identify if a given data in a pipeline in Data Science has been compromised by insecure tasks assigned as Cybersecurity test exercises. Even better in this scenario the application makes elaborate quick commentary to enable simpler iteration cycles in study.

Bringing robotic analysis together with review that involves direct interaction will ensure any learning environment and evaluation process produces steady levels of output will improve students’ scores in any group or section it seems.

Author

Dr. Yogita Gigras
Associate Professor
Department of CSE