B.Tech — Artificial Intelligence & Data Science
Final Year StudentAce Engineering College
Current CGPA
8.4
8.4 / 10.0
Available for AI / ML roles
Surya Chowdary
Aspiring AI & Data Science student with hands-on experience building end-to-end Machine Learning pipelines. Developed intelligent AI applications including StudySphere AI (RAG platform) and an automated NLP Resume Screening System. Passionate about solving real-world problems using Machine Learning, Deep Learning, NLP, Large Language Models, and Generative AI.
status: final yearCGPA 8.4
About
Engineering intelligent systems, end to end
I'm Surya Chowdary, an AI engineer in the making who is fascinated by systems that can read, reason and respond. My work sits at the intersection of machine learning research and real product engineering — from cleaning raw data and engineering features, to training and evaluating models, to shipping them as applications people can actually use.
I've built a Retrieval-Augmented Generation study assistant powered by Groq LLMs, an automated NLP resume screening platform, and a deep learning hate speech classifier. Each one taught me something about the full lifecycle: data in, insight out, deployed and measurable.
I care about clean pipelines, honest metrics and interfaces that make model output understandable. My goal is to join a team building production AI where I can keep learning fast and shipping thoughtfully.
End-to-end
ML Pipelines
3 shipped
AI Projects
LLM · RAG · NLP
Focus
Areas of interest
- Machine Learning
- Artificial Intelligence
- NLP
- Deep Learning
- Large Language Models
- RAG Systems
- Data Processing
- AI Applications
- Generative AI
Education
Academic foundation
Experience
Hands-on machine learning work
Machine Learning Intern
May 2026 – June 2026Coding Samurai
- Built Machine Learning models using Python and Scikit-Learn
- Data preprocessing
- Feature engineering
- Model training
- Model evaluation
Featured Projects
AI applications built and deployed
Retrieval-augmented generation, NLP automation and deep learning classifiers — each shipped as a usable product.
StudySphere AI
RAG + Groq LLM- RAG Platform
- LLM
- Groq
- Python
- Streamlit
- NLP
Developed a Retrieval-Augmented Generation (RAG) study assistant capable of processing uploaded documents using intelligent chunking and keyword-based context retrieval. Integrated Groq LLM to generate context-aware responses while displaying retrieved source context. Deployed using Streamlit Cloud, allowing users to interactively query study materials.
Automated Resume Screening Using NLP & ML
89% accuracy- NLP
- Machine Learning
- TF-IDF
- Logistic Regression
- Cosine Similarity
- Streamlit
Built an AI-powered resume screening platform that automates candidate ranking using TF-IDF, Cosine Similarity, and Logistic Regression. Developed an interactive Streamlit application for resume upload, matching, and automated candidate evaluation. Achieved 89% classification accuracy.
Hate Speech Detection Using Deep Learning
87.77% accuracy- Deep Learning
- MLP
- NLP
- Streamlit
- Python
Developed a hate speech detection platform using TF-IDF feature extraction and Multi-Layer Perceptron for multi-class text classification. Supports confidence visualization and CSV batch prediction. Achieved 87.77% accuracy on unseen test data.
Skills Dashboard
The stack behind the models
35 technologies across languages, frameworks, AI/ML, data science and tooling.
5
Core domains
35
Technologies
Python
Primary language
Languages
88%- Python
- Java
- C++
- SQL
Frameworks
82%- FastAPI
- Django
- TensorFlow
- Keras
- PyTorch
- Scikit-Learn
AI & Machine Learning
90%- Machine Learning
- Deep Learning
- NLP
- RAG
- Transformers
- Neural Networks
- MLP
- LLM
- NLP Embeddings
- Feature Engineering
- Cross Validation
- Model Evaluation
- Gradient Descent
- Back Propagation
- Optimization
Data Science
85%- Pandas
- NumPy
- Data Analysis
- Data Processing
Tools
80%- Git
- GitHub
- Docker
- VS Code
- Jupyter Notebook
- Streamlit
Engineering Journey
From first Python script to AI engineer
A roadmap of the skills, systems and milestones that shaped the work.
step 01
Started AI & Data Science
step 02
Learning Python
step 03
Machine Learning
step 04
Deep Learning
step 05
Natural Language Processing
step 06
RAG Systems
step 07
LLMs
step 08
AI Projects
step 09
Machine Learning Internship
step 10
Current Goal: AI / Machine Learning Engineer
Certifications
Verified learning milestones
Oracle AI Foundations Associate
Oracle
Foundational certification covering AI, ML and generative AI services.
Machine Learning
Online Certification
Supervised & unsupervised learning, model evaluation and tuning.
Deep Learning & AI
Online Certification
Neural networks, back propagation, optimization and CNN/MLP architectures.
Python Certification
Online Certification
Core Python, data structures and scientific computing libraries.
Contact
Let's build something intelligent
Open to AI/ML engineering roles, internships and collaborations.