SHREYA JADHAV

Data Analyst | AI Enthusiast
Pune, IN.

About

Highly analytical BCA graduate with a strong foundation in Data Analysis and Artificial Intelligence, eager to leverage expertise in data-driven decision-making and AI innovation within a dynamic organization. Proven ability to transform complex data into actionable insights, demonstrated through successful projects in RAG systems, machine learning, and business intelligence.

Education

Pune University (Brihan Maharashtra College of Commerce [BMCC])
Pune, Maharashtra, India

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Bachelor of Business Administration

Computer Application

Grade: Grade B+

Courses

Data Structures

Algorithms

Database Management

Software Engineering

Maharashtra State Board

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Higher Secondary Certificate

Commerce

Grade: 91%

Maharashtra State Board

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Senior Secondary Certificate

Grade: 83%

Certificates

Virtual Internship in Data Analytics

Issued By

Deloitte

Google Data Analytics Professional Certificate

Issued By

Coursera

Post Graduate Program in Data Science with Artificial Intelligence & Machine Learning

Issued By

V.I.T & Eduplusnow

Skills

Data Manipulation Libraries

Pandas, Numpy.

Databases

MySQL, MongoDB.

Development & Deployment Tools

Streamlit, Jupyter, Colab.

Programming Languages

Python.

Operating Systems

Windows.

Data Analysis & BI Tools

MS-Excel, PowerBI, DAX, SQL.

Machine Learning & AI

GPT-3.5, GPT-4, Llama 3.0, Llama 3.1, Langchain, FAISS, ChromaDB, Scikit-learn, TF-IDF, Cosine Similarity, Groq API, Retrieval-Augmented Generation (RAG).

Projects

Blinkit Data Analysis using EDA & PowerBI

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Summary

Created a dynamic multi-page dashboard using Power BI and MySQL to analyze sales, inventory, and customer data, driving real-time business insights.

Movie Recommender System using Machine Learning

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Summary

Built an end-to-end movie recommendation system using Python and content-based filtering, leveraging the TMDB 500 dataset to deliver personalized recommendations.

RAG Pipeline

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Summary

Developed an intelligent Retrieval-Augmented Generation (RAG) chatbot providing context-aware and accurate responses by integrating Langchain and Llama 3.1, enhancing information retrieval from diverse documents.