ARUN PRAKASH KATA

As a passionate and curious Computer Science graduate student, I'm eager to apply my academic knowledge in a real-world setting. I'm looking for an internship where I can contribute meaningfully, grow alongside a dynamic team, and gain hands-on experience in areas like software development, artificial intelligence, or cloud computing.

AI based banking bot - Team Leader

• As a team leader, I helped my teammates to get the resources for the project.
• This project is for the getting the information about the banking details.
• We have introduced new feature that is speech recognition in the chat bot system through NLP.

Securing resources in decentralised cloud storage - Team Leader

• This project is about the storing of our data in the cloud without any issues of security.
• As a team leader, I co-ordinated with the teammates for the resources needed for the project and the tools that are helpful for developing the project.

Ecommerce Website using python

• Developed a full-featured ecommerce web application using Django framework, implementing product catalog, detailed product views, and session-based shopping cart functionality.
• Designed and implemented data models for Products and Orders, enabling efficient management of product information and customer orders.
• Created user-friendly views and templates for product listing, cart management, and checkout process, enhancing the overall user experience.
• Configured project settings including database (SQLite), static and media file handling, and integrated Django’s built-in authentication and session management.
• Utilized Django’s MVC architecture and best practices to build a scalable and maintainable ecommerce platform.

Movie Recommendation System(Machine Learning)

• Built a movie recommendation system that suggests personalized movie choices based on user behavior using collaborative filtering.
• Used the MovieLens 100k dataset to train a user-based model that finds similar users based on rating patterns.
• Applied cosine similarity and the Surprise library to predict user preferences and generate top movie suggestions.
• Preprocessed data with Pandas and evaluated model accuracy using RMSE to ensure reliable recommendations.
• Designed the system to be modular and scalable, with the potential to expand into hybrid or content-based recommendations.

• Awarded 1st prize in the SPEED Regional competition.
• Awarded prize in volunteering the social cause.

• Certified in foundations of c.
• Certified in programming in c++.
• Certified in Machine Learning Using Python from Internshala.
• Certified in foundations of data analysis from coursera.

• C
• C++
• Java
• Python
• Database
• Data Analysis
• Machine Learning

Reading books

playing sports

music