AI / ML  ·  Full Stack Developer

Vanga Manikanta
Varaprasad

B.Tech CSE (AI & ML) student with hands-on experience in full-stack web development and a strong foundation in Machine Learning, NLP, and Generative AI. Passionate about building intelligent software solutions and seeking an entry-level AI/ML or Full Stack Developer role.

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Mission Log

About Me

  • Location Warangal, Telangana
  • Phone +91 9550219092
  • Email manikantavaraprasadvanga00@gmail.com
  • LinkedIn manikanta-varaprasad-vanga
  • GitHub manikantavaraprasad2130

I'm a B.Tech CSE (AI & ML) student with hands‑on experience in full‑stack web development and a strong foundation in Machine Learning, NLP, and Generative AI.

Proficient in the MERN stack, RESTful APIs, and data‑driven application development — I'm passionate about building intelligent software solutions and currently seeking an entry‑level AI/ML or Full Stack Developer role.

Trajectory

Education Timeline

B.Tech – Computer Science & Engineering (AI & ML)

SR University, Warangal · Aug 2023 – May 2027

CGPA: 6.50 / 10

Intermediate – MPC

Samatha Junior College, Telangana · 2021 – 2023

Score: 779/1000 (77.9%)

SSC

Sharada High School, Telangana · 2021

GPA: 9.3 / 10

Tech Constellation

Skills & Tools

Languages

PythonJavaJavaScript (ES6+)

AI / ML

Machine LearningNLPGenerative AI NumPyPandasScikit-learn

Frontend

ReactJSHTML5CSS3Responsive UI

Backend

Node.jsExpress.jsREST APIsMVC

Databases

MongoDBSQL

Tools & Platforms

GitGitHubVS Codenpm VercelRenderStreamlit Cloud

Core Concepts

DSAOOPDBMSOSComputer Networks
Launch Pad

Featured Projects

Nestora Connect

MERN

A full‑stack rental platform connecting property owners and customers across India for property listing and rental inquiries. Owners upload property details and images; customers contact owners directly for rental needs. Implemented image upload with Multer and RESTful APIs with MongoDB, deployed via Vercel (frontend) and Render (backend).

React.jsNode.jsExpress.jsMongoDBMulter

Student Result Predictor

ML

An ML web app using a Random Forest Classifier achieving 87% accuracy to predict student pass/fail outcomes, processing 1,000 student records across 12 features (attendance, study hours, subject scores). Features a 3‑tab interactive dashboard with real‑time predictions, analytics, and model insights using Plotly, deployed live with personalized recommendations for at‑risk students.

PythonScikit-learnStreamlitPlotlyPandas
Signal Boost

Certifications & Strengths

Microsoft Certified

Azure AI Fundamentals

Problem Solving Analytical Thinking Team Collaboration Leadership Effective Communication Adaptability Time Management
Transmission

Let's Connect

Open to entry‑level AI/ML and Full Stack Developer opportunities. Reach out — I'm ready for launch.