Pushkar Khattri

As a VOIS for Tech intern, I explored Conversational Data Analytics using LLMs, focusing on leveraging AI for insight extraction and automation across domains such as agriculture, science, and business operations. The program emphasized applied learning through technical sessions, case studies, and hands-on projects using data analysis and conversational AI frameworks. I developed an understanding of integrating LLM-based systems for data-driven applications, improved analytical modeling techniques, and worked collaboratively with mentors to present domain-specific insights. This experience enhanced my skills in LLM-based analytics, data processing, and AI communication systems.

As a Front-End Web Development Intern under the AICTE–Edunet Foundation SkillsBuild Program, I focused on designing and developing responsive, user-centric web interfaces using modern frontend technologies. The internship emphasized mastering HTML, CSS, and JavaScript fundamentals along with exposure to frameworks like React.js and Tailwind CSS through a structured, mentor-led project. Over the six-week program, I participated in weekly technical sessions, completed hands-on coding assignments, and independently developed a capstone project applying design principles, accessibility, and performance optimization. This experience enhanced my skills in UI/UX design, responsive web architecture, and modern frontend workflows, while also improving collaboration, project presentation, and agile learning capabilities.

During my internship at IBM SkillsBuild, I developed and deployed complete machine learning pipelines on IBM watsonx.ai and IBM Cloud for AgriTech and Healthcare applications, achieving around 98% model accuracy with a 30% reduction in latency. I worked extensively on building Agentic AI systems using Granite LLM, LangGraph, and RAG architectures to automate research and healthcare workflows. Alongside, I performed data cleaning, visualization, and statistical analysis on national-scale datasets, producing actionable insights and reports. I also created AI chatbots and cloud automation flows, earning certifications in LangChain RAG Lab, AI Foundations, and Cloud Solutioning.

As an AI Intern at Mirai School of Technology, I focused on designing automation workflows powered by AI to optimize daily business processes. I built an AI-integrated system connecting Google Forms, Sheets, and Gmail, reducing manual data handling by 90%. Additionally, I developed a Computer Vision Waste Classification model using Google Teachable Machine with 85% real-time accuracy. My work also included developing and deploying interactive AI web applications using Lovable, Streamlit, and Gradio. For my capstone, I created an AI Travel Planner powered by Gemini AI and n8n that automated personalized itinerary generation and email delivery, demonstrating the potential of end-to-end workflow automation.