B.E. graduate in Artificial Intelligence & Data Science
B.E. graduate in Artificial Intelligence & Data Science with hands-on experience in machine learning, computer vision, NLP, and data analytics. Proficient in Python and experienced in building end-to-end AI/ML projects involving RAG, computer vision, customer behavior analytics, LLMs, LangChain, and vector databases.
IBM SkillsBuild
June 2024 – August 2024
Completed comprehensive training in data analytics using Python, Pandas, NumPy, and Microsoft Excel; practiced data cleaning and preprocessing, including missing-value handling, outlier detection, and feature encoding; created visualizations with Matplotlib and Seaborn; applied exploratory data analysis and data manipulation techniques.
TNS Foundation
July 2025 – September 2025
Completed structured Artificial Intelligence and Machine Learning training using Python from fundamentals to advanced concepts; covered Python, NumPy, Pandas, and Matplotlib; completed hands-on mini-projects involving data collection, preprocessing, model training, and evaluation.
Bachelor of Engineering, Artificial Intelligence & Data Science
June 2022 – May 2026
Relevant coursework: Machine Learning, Deep Learning, Data Structures & Algorithms, Data Analytics, Python Programming, Database Management Systems, Cloud Computing
Engineered a multi-modal AI pipeline using OpenAI Whisper, LangChain, Mistral AI, and ChromaDB to generate summaries, action items, decisions, and key questions from video content. Designed a RAG architecture for semantic search and context-aware Q&A over transcripts and built a Streamlit dashboard with AI inference, KPI metrics, and multi-turn chat.
Developed a student performance prediction system using a dataset of 25,000 records. Performed preprocessing, missing-value handling, categorical encoding, and feature scaling; trained Regression Tree, Logistic Regression, and KNN models; evaluated performance using MSE, MAE, and R2 score, achieving 85% prediction accuracy.