Hey! I'm Adnan Sattikar


Pre-Final Year Engineering Student pursuing Integrated Mtech in CSE at VIT Vellore.
I`m a Full Stack Web Developer and currently exploring AI-ML Technologies using JavaScript

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about me

As a pre-final year Computer Science Engineering student at VIT Vellore, I possess a strong command of Java programming and hands-on experience crafting visually appealing, scalable and efficient Full Stack Apps using MERN Stack.

My passion for cricket extends to analytics, where I explore data analytics to gain insights into the game. I have hands-on experience developing Web Scrapers for data collection and analysis. My research domain involves delving into machine learning techniques and fan sentiment analysis to construct predictive models for cricket matches.

Currently serving as the Secretary of the Rotaract Club of VIT, I leverage this role to further enhance my soft skills, showcasing leadership and organizational abilities. This combination of technical proficiency and soft skills positions me as a valuable contributor ready to make a significant impact on any team or project

As a dedicated and ambitious Computer Science Engineer, I am eager to explore new opportunities to contribute to the Software and IT industry, and enhance my overall skillset . With a keen interest in continuous learning and innovative problem-solving, I am confident in my ability to make significant contributions to any team or project.

Languages
Java, Python, JavaScript, Typescript
Frameworks
React, Angular, Express
Databases
MySQL, MongoDB
WebServices
AWS, IBM Cloud
Data Analytics
bs4, PowerBI
AI ML
Tensorflow, OpenCV, IBM Watson
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Languages : Hindi, English, Kannada, Marathi

Phone : +91 9739711669

Email : adnan.sattikar2001@gmail.com

Experience

Full Stack Web Developer Intern @ Astral Securitas: Internship (Jun'22-Jul'22)

# Spearheaded front-end design and development, transforming concepts into a user-friendly and visually appealing interface.
# Developed an efficient automated email sending system, reducing manual workload and enhancing communication within the company.
# Managed deployment, hosting, and ongoing maintenance of digital solutions, ensuring reliability, scalability, and optimal performance on Hostinger.

Secretary @ Rotaract Club Of VIT (NGO) (Mar'22-Present)

# Volunteer - "Teaching The Needy" . Weekly visits to schools to educate underprivileged children.
# Video Editing & Content Creation Team

Education

Integrated Mtech CSE VIT University 2020-2025

Grade: 8.98 / 10.00
Merit scholarship for the Academic Years 2022-23 and 2020-21

Grade 11-12: KLE Independent PU College, Belgaum, Karnataka 2018-20

Grade: 92.3%
Activities and societies: Participated in District Level Table Tennis Tournaments.

Certifications

IBM Artificial Intelligence Analyst

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Portfolio

Aqua Treat Systems WebApp

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This application consists of a frontend built with React.js, offering features like displaying home products, contact form, and an admin dashboard for managing customer details. The frontend utilizes technologies like React Router, Fetch API, Moment.js, Lodash, and Bootstrap.

The backend is built with Node.js and Express.js, using MongoDB Atlas as the database. It provides API endpoints for managing customers, products, messages, and contact forms. Authentication is implemented using JSON Web Tokens (JWT), and Twilio API is used for automated customer message notifications. The MERN Webapp of Aqua-Treat-Systems offers a seamless user experience, providing customers with a user-friendly interface to explore products and interact with the company.

Tech Stack: MERN

WPL Dream Team Predictor

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In this project, I delved into the realms of Data Analytics and Data Visualization, meticulously analyzing and extracting valuable insights from the tournament's data. By examining player performances, team strategies, and match outcomes, I uncovered key patterns and trends that can significantly impact future editions of the WPL.

Using advanced statistical modeling techniques, this project helps teams in making data-driven decisions before and during matches. The project also involved the creation of intuitive and visually appealing dashboards, enabling coaches, players, and analysts to grasp crucial performance patterns at a glance.

Tech Stack: PowerBI, PowerQuery Pandas, bs4

Handwritten Digits Classifier

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The Handwritten Digits Classifier project focused on implementing a powerful deep learning model using a Deep Convolutional Generative Adversarial Network (DCGAN) and TensorFlow. The objective was to accurately classify handwritten digits from the MNIST dataset.

The DCGAN architecture consisted of a generator network that generated realistic digit images and a discriminator network that learned to differentiate between real and fake digits. Both networks were trained using TensorFlow, and the project achieved high accuracy in recognizing and classifying handwritten digits.Overall, this project showcased artificial intelligence, deep learning, and neural networks technologies while highlighting the ability to develop innovative solutions for image classification tasks.

Tech Stack: AI, ML, DL, CNN, GANs

Contact Me