I am a Computer Science & Data Science student who enjoys understanding how technology works and turning what I learn into practical solutions.

My main interests are Artificial Intelligence, Machine Learning, Generative AI, Backend Development, Data Analytics, and Cloud Technologies.

Rather than limiting myself to one area, I like working across the complete problem-solving process — understanding the problem, working with data, building the model or application, developing APIs, and making the solution usable.

• 🎓 B.Tech Computer Science & Data Science student at JNTU-GV
• 💻 Interested in AI/ML, Generative AI, Backend Development and Data
• 🐍 Comfortable working with Python, SQL and Java
• 🤖 Building applications using Machine Learning, RAG, LangChain and FAISS
• ⚙️ Developing backend services using FastAPI and REST APIs
• 🗄️ Working with PostgreSQL for data storage and application development
• 📊 Creating data-driven dashboards using Power BI and DAX
• ☁️ Exploring Cloud Computing and OCI
• 🐳 Using Docker, Git and GitHub for development and project management

I am particularly interested in projects where different areas of technology come together.

I enjoy building practical AI applications rather than working only with theory.

Some areas I have explored:

• Machine Learning applications
• Generative AI
• Retrieval-Augmented Generation (RAG)
• Semantic Search
• Vector Databases
• LangChain
• FAISS

I like turning models and ideas into usable applications through:

• FastAPI
• REST APIs
• PostgreSQL
• Docker
• Modular application design

I also enjoy understanding data and converting it into useful information through:

• SQL
• PostgreSQL
• Power BI
• DAX
• Data Visualization
• Business Analytics

A Generative AI application that allows users to ask questions about PDF documents and receive context-aware answers using Retrieval-Augmented Generation.

Built with: Python, LangChain, FAISS, RAG, FastAPI

An end-to-end Machine Learning application that predicts customer churn and generates personalized retention recommendations.

Built with: Python, Scikit-learn, FastAPI, PostgreSQL, Docker

An interactive analytics solution for understanding SaaS revenue, customer churn, retention and subscription performance.

Built with: PostgreSQL, SQL, Power BI, DAX

Languages

Python · Java · SQL

AI / ML

Machine Learning · Scikit-learn · Generative AI · RAG · LangChain · FAISS · Pandas · NumPy

Backend

FastAPI · REST APIs · PostgreSQL

Data & Analytics

Power BI · DAX · Streamlit · Data Visualization

Cloud & Tools

Oracle Cloud Infrastructure · Docker · Git · GitHub · VS Code

I believe that learning technology is most valuable when it leads to something that can actually be built, tested and improved.

So whenever I learn a new concept, I try to take it beyond notes and tutorials and use it in a project.

I am currently focused on becoming better at:

Writing better code → understanding systems → building useful applications → learning from real problems.

• Generative AI applications
• RAG systems and AI-powered search
• AI agents and intelligent applications
• Cloud-based application development
• Backend engineering
• Data Engineering
• Production-oriented AI systems

B.Tech – Computer Science & Data Science
JNTU-GV
CGPA: 8.3 / 10

• Oracle Cloud Infrastructure (OCI) AI Foundations Associate
• IBM AI Fundamentals
• Deloitte Australia – Data Analytics Job Simulation
• JPMorgan Chase & Co. – Quantitative Research Virtual Experience

📧 Email: preethiberi2611@gmail.com

💼 LinkedIn: Connect with me

💻 GitHub: Explore my projects

I am still a student, and I don't claim to know everything.

What I do have is curiosity, consistency, and the willingness to learn by building.

My goal is to keep improving one project, one concept and one problem at a time — and eventually build technology that is genuinely useful.