Machine Learning Data Science

Ashlesha Patil

***************@*****.*** +1-734-***-**** Ann Arbor, MI

Education

Master of Science (Physics – Material Science)

K.B.C. North Maharashtra University, Jalgaon, Maharashtra, India (2018-2020) Bachelor of Science (Physics)

JET’S Z.B. Patil College, Dhule, Maharashtra, India (2015-2018) Higher Secondary Education

Jai Hind Junior College, Dhule, Maharashtra, India (2014-2015) Skills

• Data Analysis & Visualization - Proficient in Tableau, Power BI, and Matplotlib.

• SQL & Database Management - Knowledge in writing queries and data extraction.

• Excel - Skilled in Pivot Tables, VLOOKUP, and data cleaning.

• Python -Familiar with NumPy, Pandas, and basic data manipulation.

• Statistical Analysis - Knowledge of hypothesis testing, regression.

• Machine Learning - Familiar with machine learning concepts, including decision trees and their applications.

• Data Cleaning & Preprocessing - Hands-on experience in handling large datasets efficiently.

• Other- MS Word, MS Powerpoint, Google Sheets.

Work Experience

Subject Matter Expert (Physics) at CloudBird Digital Pvt. Ltd. (June2022)

• Created high-quality, accurate Physics solutions for the Text Solution Process in compliance with strict guidelines.

• Applied analytical and problem-solving skills to precise content.

• Utilized tools like Google Sheets and Microsoft Word to deliver solutions and ensure content accuracy. Certifications

• Diploma in applied data science - Loyola Institute Of Business Administration(LIBA), Chennai

• SQL for Data Science - Coursera

• Data Analytics using Excel - Great Learning

• Tableau For Beginners - Great Learning Academy

• Python for Data Analysis - Udemy

Projects & Academic Experience

Master’s Project - Light Amplification by Stimulated Emission of Radiation- Working and Applications of Laser. Bachelor’s project - Interesting About Indian Satellite and Spacecraft- Working and Applications of Satellites and Spacecraft.

Diploma project -

• Customer Sales Analysis using SQL & Tableau - Analyzed sales data, created dashboards, and identified trends.

• Data Cleaning in Python - Processed raw data, handled missing values, and prepared datasets for analysis.

• Excel-based Inventory Management - Built a dynamic dashboard for stock tracking and sales forecasting.

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