Synopsis

HCLTech and Economic Times hosted an eight-hour AI Masterclass for engineering students. Around 300 students learned about AI-assisted development and large language models. They explored AI agents and cloud deployments, including AWS Bedrock. Students were encouraged to build AI projects to demonstrate their skills. The masterclass emphasized practical application and continuous learning in AI.

On 8 August, HCLTech and Economic Times conducted an eight-hour online AI Masterclass for second, third and fourth-year engineering students, designed to equip them with the artificial intelligence (AI) skills needed to become industry-ready. Around 300 students from 70 colleges, selected as campus ambassadors, alongside top performers of AMPlified – The AI Challenge participated in the masterclass.

Opening the masterclass, HCLTech’s Corporate Vice President & Global Head of Digital Business, Pawan Vadapalli, emphasised that skills in the AI era goes beyond coding. Students, he said, need to learn how to frame problems, understand business context, communicate ideas and exercise engineering judgement. “AI can make coding faster,” he noted, “but it does not remove the need for engineering thinking.”

The masterclass moved progressively from fundamentals to advanced AI development. Students began with AI-assisted software development using GitHub Copilot, learning how AI can help write, explain and test code, including edge cases, while also understanding why code quality, security and maintainability matter, not merely speed of development.

The sessions then moved into large language models (LLMs), embeddings and Retrieval-Augmented Generation (RAG). Students explored tokenisation, context windows, hallucinations, document loaders and text splitting before building knowledge-aware applications. A financial RAG use case demonstrated how enterprise applications can ground LLM responses in proprietary information.

The final modules introduced students to AI agents, Agentic architectures and cloud deployments including LangChain, LangGraph, multi-agent systems and Model Context Protocol (MCP), along with an introduction to AWS Bedrock. They also explored practical applications, such as code-review agents, and learnt when to use LangChain as opposed to LangGraph.

One of the central concerns among students was accessing new pathways to stay relevant as the technology and career landscape evolves, whether by continuing to build their AI capabilities or deepening their understanding beyond the classroom.. They were encouraged to focus on AI infrastructure, including databases, memory, guardrails and deployment, while building a strong foundation in programming, DSA, system architecture and LLM fundamentals. A recurring message throughout the session was that the best way to learn AI is by building.

Pawan also stressed that technology would evolve rapidly, but the traits employers value will remain constant: curiosity about what is happening in AI, evidence of having built things independently, agility in responding to challenges, and the passion to keep learning.

The interactive masterclass also saw students raise questions around AI and data sovereignty, sustainability of AI infrastructure and the environmental impact of data centers. Pawan highlighted sustainability as an organisational culture and spoke about HCLTech’ s focus in this area.

The masterclass concluded with students being tasked to submit two AI projects to qualify for their completion certificates, putting the emphasis firmly on learning by building rather than learning by listening.

This masterclass was conducted as part of the ET Masterclass-HCLTech AI Skills for the Future series for B.E./B. Tech engineering students.