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Hello, I'm

Harsh Pilania
Data Science & Analytics Professional

Data Science graduate specializing in AI-powered applications, RAG systems, and LLM-based solutions. Skilled in building intelligent learning platforms and automated analysis tools using Python, SQL, and modern AI technologies to solve real-world problems.

Harsh Pilania
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About Me

I am a Data Science graduate driven by curiosity and a passion for creating impactful solutions through data and artificial intelligence. My career is focused on the intersection of data science, analytics, and AI innovation, where I combine technical expertise with creative problem-solving to deliver meaningful results.

My technical foundation spans Python, SQL, Machine Learning, Generative AI, and LLMs, complemented by experience with analytics tools like Power BI and LangChain. I thrive in collaborative environments, working closely with cross-functional teams to translate complex data into clear, actionable insights that drive strategic decisions.

I am passionate about exploring emerging frontiers in artificial intelligence and data science while developing innovative applications that deliver meaningful value.

Tools I Work With

Python Python
SQL SQL
Power BI Power BI
Machine Learning Machine Learning
Generative AI Generative AI
LangChain LangChain
Hugging Face Hugging Face
NLP NLP
RAG RAG
AI Agents AI Agents

Professional Experience

Digital Analytics Intern

Cognizant Technology Solutions, Coimbatore

April 2025 - August 2025 • 5 months

  • Collaborated with a team on a project to analyze website traffic, focusing on data analysis and building insightful dashboards using Google Analytics
  • Worked with tools like Python, SQL, Power BI and Looker Studio to derive business insights
  • Successfully delivered the project by transforming raw data into actionable insights through interactive dashboards
Python SQL PowerBI Google Analytics

Featured Projects

Practical applications of LLMs and GenAI technologies

🎯

Notes AI

Built a multi-source AI learning platform that transforms YouTube videos, PDFs, and web pages into an intelligent tutoring system. Implemented RAG architecture with FAISS and OpenAI embeddings for contextual Q&A, automated summarization, and quiz generation with conversational memory.

Python Langchain OpenAI Groq
📈

Resume AI

Built an interactive ATS resume evaluation platform in Streamlit that analyzes resumes against job descriptions and provides compatibility scores. Integrated RAG architecture with FAISS, OpenAI embeddings, and LLaMA 3.3 for skills gap detection, personalized career advice, and real-time optimization feedback.

Python Lagchain OpenAI Embeddings Cosine Similarity
🛒

Blog Agent

Built a multi-agent AI system in Streamlit that automates blog content creation from trending topics to publication-ready posts. Integrated Reddit API for topic discovery, OpenAI GPT-4 for content generation, and DALL-E 2 for image creation.

Python Reddit API OpenAI DALL-E2
🤖

WebRAg-BOT

Built a RAG-powered chatbot using Streamlit that enables conversational interaction with web content. Integrated LangChain for document processing, FAISS for vector storage, and Groq's LLaMA 3.3 for responses. Features real-time web scraping, intelligent text chunking, conversational memory, and chat-style UI for natural Q&A with any webpage content.

LangChain BeautifulSoup FAISS LLaMA
💰

ChatDB

Developed a conversational SQL agent using Streamlit that enables natural language querying of MySQL databases. Integrated LangChain SQL toolkit with Groq's LLaMA 3.3 for intelligent query generation and execution. Features secure database connections, conversational memory, real-time streaming responses, and comprehensive error handling for seamless database interactions.

Python Langchain SQL toolkit Groq
🌐

AgentCore

A multi-source search agent that acts as your personal research assistant, instantly gathering information from web search, academic papers, news, videos, and weather data through a single conversational interface. Built with modern AI frameworks to intelligently select the best information sources and maintain context across conversations.

Python Agents Wikipedia and Arxiv Wrapper DuckDuckGo