Divya Pardeshi

I'm

About

Hi, I'm Divya Pardeshi an ex-olympiad teacher diving into the dynamic world of data science. With a teaching background and over 1 year of internship experience in data science & data analysis, I thrive on transforming raw data into strategic insights using Python, SQL, and Tableau. My goal is simple: harnessing data's potential to drive impactful decisions and innovative solutions. Let's collaborate and unleash the power of data-driven possibilities.

City: Electronic City, Bengaluru

Email: divyapardeshi20@gmail.com

Interests

Data Science

Machine Learning

Artificial Intelligence

Natural Language Processing

Computer Vision

Data Visualization

Statistics

Data Analysis

Education

Master's Program In Data Science

August 2022 - November 2023

Relevant Coursework

Data Science With Python
Machine Learning
Deep Learning with Keras and Tensorflow
SQL
Tableau

M.Sc in Mathematics

July 2014 - August 2017

Relevant Coursework

Linear Transformations
Numerical Analysis
C++ Programming

Certifications

Master's Program in Data Science by Simplilearn

Certificate Course On Data Science by NASSCOM

Data Science Using Python Programming by 360DigiTMG

Artificial Intelligence & Deep Learning by 360DigiTMG

Advanced Excel by Codebasics

Power BI by Codebasics

Data Visualization Using PowerBI by 360DigiTMG

Data Visualization Using Tableau by 360DigiTMG

Python Fundamentals by NASSCOM

SQL by 365 Data Science

The Machine Learning Process A-Z by 365 Data Science

Statistics by 365 Data Science

Probability by 365 Data Science

Experience

iNeuron.ai

August 2023 - Present

Data Science & Analytics Intern

Engineered interactive dashboards, elevating actionable insights by 30% and enabling robust data analysis for informed decision-making while contributing to data science projects through machine learning techniques and data visualization tools.

Innodatatics

February 2023 - August 2023

Data Science Intern

During this internship, I developed a time series demand forecasting models to tackle inventory management challenges within a hospital pharmacy. The project's core objectives were to minimize stockouts, optimize inventory, and prevent prescription returns.
Implemented advanced machine learning techniques for precise demand prediction.
Utilized Streamlit to deploy models on the web, ensuring easy access for informed decision-making.
Enabled data-driven ordering decisions, effectively reducing shortages, and significantly enhancing efficiency in managing pharmacy inventory.