Sql
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Python
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Data Visualization
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Statistical Analysis
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Machine Learning
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Market Research
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Sql
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Python
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Data Visualization
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Statistical Analysis
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Machine Learning
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Market Research
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Sadi Gyan Lokesh is a dedicated data science professional with extensive experience as an intern at Netzwerk Data Science Intern Private Limited, where he honed his skills in machine learning algorithms and data science projects. He possesses a robust educational background, including a Bachelor of Technology in Mechanical Engineering from Suddhananda Group of Institution College of Engineering, complemented by a diploma from Centurion University of Technology & Management. Sadi's proficiency in SQL, Python, data visualization, and statistical analysis allows him to excel in market research and predictive modeling. He aims to leverage his advanced skills in English, Hindi, and Telugu to drive impactful data-driven solutions in the tech industry.

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Skills

Sql
Python
Data Visualization
Statistical Analysis
Machine Learning
Market Research

Experience

Data Science Intern

Dec 2022 – Jun 2023

(7 Months)

Netzwerk Data Science Intern Private Limited

Worked on data science projects and applied machine learning algorithms.

Education

Bachelor of Technology (Mechanical Engineering)

2020 - Present

Suddhananda Group of Institution College of Engineering

Diploma

2015 - Present

Centurion University of Technology & Management

Matriculation

2014 - Present

Kendriya Vidyalaya Khurda Road

Languages

No languages listed.

Projects

Project #1

House Price Prediction Using Machine Learning

House price prediction can help the developer determine the selling price of a house and can help the customer to arrange the right time to purchase a house. Tools used: Pandas, Matplotlib, Seaborn.

Project #2

Data Analysis on Weather Forecast

The window best matched is made to participate in the process of predicting weather conditions. Tools used: Python, Matplotlib.

Project #3

Data Analysis on Heart Diseases

A dataset is selected from the UCI repository with patient's medical history and attributes. By using this dataset, we predict whether the patient can have a heart disease or not. Tools used: Python, Matplotlib, Support Vector Machine(SVM).

Certificate

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Advance Data Science

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Artificial Intelligence