Jenishda portfolio

about me

SSN YRC

student volunteer

SSN

participated 4+ workshops

NPTEL

obtained two certifications

GHSS

10+ awards won

my name is Jenishda

A full-stack developer , SQL enthusiast. I'm currently pursuing my bachelor's in Computer Science and Engineering from SSN College of Engineering.

contact me

SQL 90%

Power BI 75%

Data Science 80%

HTML 95%

CSS 80%

javascript 65%

my certifications

Guvi

Build a Face Recognition Application using Python

Eduonix

Become a Certified Web Developer from Scratch

HackerRank

SQL (Intermediate)

Introduction to Data Science

Great Learning

Data Structures in C

Sololearn

Introduction to Java

my project

Scholarship Management System

The project “Scholarship Management System” is developed by using HTML, CSS, Java script as a front end and Servlets, MySQL as a back end. This project is used to reduce the manual work by using computerized work to maintain the scholarship related information related to students.

Uber Trip Analysis

It aims to develop to track and monitor the performance of the drivers, vehicles, and overall operations. We can visualize key metrics such as trip completion rates, driver ratings, average trip duration, and customer satisfaction scores to identify areas for improvement and make data-driven decisions using Power Bi tool.

Meesho - Online Textile Industry

This project aims at to monitor all process in the single platform, like order receiving, delivery etc. As these works are done manually at the stores at present it takes a lot of time to complete the work. So, the basic aim of the project is to develop a system, which is very simple, user friendly, easy retrieval and simple access using SQL.

Online Bank Management System

The main objective is to create a web-based only system. which will help to maintain the bank account records, Maintain the transaction records of the customers. Easy to track all the banking activity a centralized system to maintain all the bank activity using Java.

Milk Quality Prediction

It helps us to build machine learning models to predict the quality of milk. This dataset consists of 7 independent variables ie pH, Temperature, Taste, Odor, Fat, Turbidity, and Color. Generally, the Grade or Quality of the milk depends on these parameters.

Jenishda

Jenishda Pushpa Mary S