High School Full-Stack

Saipranay Gattu

Vill:Dubyala, Mdl:Tekumatla, Dist:Jayashankar(Bhupalpally), Telangana, 506356 770-***-**** ad8jms@r.postjobfree.com

https://www.linkedin.com/in/saipranay-goud-3b750823a https://github.com/GattuSaipranay

EDUCATION

Nxtwave Disruptive Technologies

Industry Ready Certification in Full-stack Development Sep 2022 - Ongoing

Vaagdevi Engineering college, Warangal

B Tech (Bachelor of Technology)_Computer Science Engineering (CSE) (7.0 CGPA) 2020 - 2024

Shivani Junior College, Hanmakonda

Intermediate_MPC (7.9 CGPA)

2018 - 2020

Blue Bells High School, Karimnagar

Secondary School Of Certificate (8.8 CGPA)

2017 - 2018

SKILLS

Frontend: HTML, CSS, Bootstrap, JavaScript, React.js Backend: Python, Express, Node.js

Databases: SQLite

PROJECTS

Food Munch (pranayrestarent.ccbp.tech)

Discover the world of food with this responsive website that showcases a comprehensive list of food items.

● Designed with a user-centric approach, this website features HTML structure elements and Bootstrap components to ensure a seamless experience.

● Get a closer look at the food items with product videos, available at the click of a button. Technologies used: HTML, CSS, Bootstrap

Todos Application (timetablesunny.ccbp.tech)

A task management solution, designed to make life easier.

● Streamlined task management through a combination of HTML, CSS, and Bootstrap for an intuitive interface.

● Seamless CRUD operations through JavaScript event listeners and dynamic UI updates.

● Secure task persistence with local storage methods, ensuring that your tasks are always available. Technologies used: HTML, CSS, JS, Bootstrap

Typing Speed Test (saipranaytyping.ccbp.tech)

An application to evaluate and improve your typing speed.

● Utilizes JavaScript and REST APIs to fetch and display the paragraph, and dynamically update the timer.

● Provides a user-friendly interface to display the typing speed and accuracy. Technologies used: HTML, CSS, JS, REST API Calls, Bootstrap Automating Mushroom Identification With Deep Learning My project uses deep learning and transfer learning techniques to automate the identification of mushroom species based on images. The focus is on three main categories: Boletus, Lactarius, and Russula. You're leveraging pre-trained models like Inception V3, Resnet50V2, and Xception to classify mushrooms into their respective species. The goal is to develop a high-performance classifier that can accurately identify mushrooms using images, which is useful for various applications like food, medicine, and research. The project concentrates on mushrooms with visible caps, gills, and stems in the images. Technologies used: HTML, CSS, JavaScript, Bootstrap, sql ACHIEVEMENTS

Co-convener SPYRO 4.0

As the Co-Convener of Spyro 4.0, an IEEE Chapter event, I successfully co-led the planning and execution of a major technical event, managing a team of volunteers and collaborating with industry experts. I contributed to program development, oversaw logistics, led marketing efforts, and assisted in financial oversight to ensure a high-quality, engaging event. IEEE Volunteer

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