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shinde-chandrakant/README.md

Hi 👋, I'm Chandrakant Shinde

SDE | Data Science Engineer

Software Engineer and aspiring Data Engineer with around 2 years of experience in designing, developing, and implementing software solutions. Proficient in coding and programming. Skilled in analyzing systems and identifying areas for improvement. Demonstrated ability to brainstorm and create innovative tools and applications. Experienced in collaborating with cross-functional teams

Skills: Java / Python / SQL / Spring / NoSQL / Flask / FastApi / AWS / Hadoop / Hive / Spark / Databricks / Kafka / Redshift / ETL

Connect with me:

emchandrakant chandrakant-shinde shindechandrakant emchandrakant @chandrakant-shinde emchandrakant

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  1. online-advertising-platform online-advertising-platform Public

    Online Advertising Platform - a comprehensive big data project

    Python

  2. BigData-Ops-on-TLC-Yellow-Taxi BigData-Ops-on-TLC-Yellow-Taxi Public

    Analysed New York City's Yellow taxi data set with Big Data tools such as Hadoop, HBase, Sqoop, MapReduce and AWS Cloud Infrastructure.

    Python 3 1

  3. BANK-ATM-ETL BANK-ATM-ETL Public

    Spar Nord, a Danish bank, optimizes ATM refill frequency by observing withdrawal behavior and dependent factors. The project builds a batch ETL pipeline to load the data into Redshift Data Mart for…

    Jupyter Notebook 2 2

  4. University-Courses-and-Applicant-Management University-Courses-and-Applicant-Management Public

    Web Application for managing university courses and applicants, allowing users to search for programs, apply online, and manage course offerings. Utilized technologies such as Spring Boot, Swagger …

    JavaScript 2

  5. Vaccination Vaccination Public

    A backend application for managing user vaccination information and vaccination center details. Utilized technologies such as MySQL, RESTful APIs, microservices architecture, load balancers, and Hy…

    Java 1 1

  6. Lead-Scoring-Case-Study Lead-Scoring-Case-Study Public

    X Company needs help selecting the most promising leads. The goal is to build a model that can rank leads based on their likelihood to buy their product or service. This is called lead scoring and …

    Jupyter Notebook