AI/ML Development Intern Candidate - Surya Dev Singh Thakur

SURYA DEV SINGH THAKUR

+91-939******* ************************@*****.*** Surya Dev Singh Thakur - LinkedIn GitHub SUMMARY

Data Science and GenAI professional with a completed PGP and B.Tech in AI & ML, specializing in Python, SQL, and AWS SageMaker for scalable model deployment. Proficient in engineering end-to-end ML pipelines and applying rigorous statistical methods to drive automated data cleaning and reproducible reporting. I bring a unique blend of technical rigor and disciplined leadership—honed through competitive sports and academic coordination—to deliver resilient, team-focused AI solutions. SKILLS

Programming Languages: Python, SQL (MySQL),C,HTML, CSS. Machine Learning: Regression, Clustering, PCA, NLP, Transformers, Prompt Engineering, Neural Networks.

Tools & Frameworks: AWS SageMaker, Stream-lit, TensorFlow, Keras, Scikit-learn, OpenCV, Pandas, NumPy.

Visualization: Tableau, Matplotlib, Seaborn.

PROJECTS

• Yelp Business Rating Prediction Using Machine Learning: Link

Problem Statement: Businesses struggle to understand which factors influence Yelp ratings and how to improve customer satisfaction. The project aims to predict business ratings using data science and generate actionable recommendations with Generative AI.

• Developed a rating prediction pipeline using NLP (TF-IDF) and ML, integrating GenAI to automatically generate actionable business improvement strategies. Tools: Python, Streamlit, NLP, Generative AI.

• Social-Media Network Filtering Using Machine Learning: Link

Problem Statement: This project was made to ensure secure delivery of trusted video content. Integrated user trust levels, intelligent agents, and video integrity checks to enhance security, authenticity, and overall trustworthiness in content sharing.

• Built a content security system using Neural Networks and user trust scores to classify video integrity, ensuring the secure delivery of trusted media.

Tools: Python, TensorFlow, OpenCV, Scikit-Learn.

• Brain Tumour Classification Using Deep Learning: Link

Problem Statement: This is an Accurate detection of brain tumours from MRI scans is critical for early diagnosis and treatment planning. Manual classification is slow and error-prone, requiring an automated deep learning approach to improve speed and reliability.

• Designed a CNN-based deep learning model to classify MRI scans, automating tumour detection to support faster and more accurate medical diagnoses.

Tools: Python, Keras, TensorFlow, OpenCV.

EDUCATION

Degree Specialization Name of the Institution Percentage / CGPA

Year of

Passing

Post

Graduation

Data Science &

Gen AI

Great Learning - 2026

B.Tech CSE (AI & ML)

Holy Mary Institute of Technology

& Science

72% 2025

12th MPC Narayana Junior College 65% 2021

10th SSC St. Patrick’s High School 69% 2019

CERTIFICATIONS

• Data Science Using GenAI [ Great Learning PGDSE]

• SQL Programming [ MindLuster ] Link

• Machine Learning with Python [ freecodecamp ] Link

• AI Job Simulation [ Cognizant Virtual Experience Program (Forage) ] Link

• Data Analytics & Visualization [ Accenture Virtual Experience Program (Forage) ] Link

• Data Science Using Python [ Brain O Vision Workshop ] Link LEADERSHIP & ACHIEVEMENTS

• Academic Leadership: Elected Class Representative (2022–2023), acting as the primary liaison between faculty and students to coordinate schedules and academic events.

• Competitive Sports: Secured 2nd Prize in both the YMCA Basketball Competition and Interschool Basketball Competition, demonstrating discipline and teamwork.

• Healthcare AI Engagement: Selected to attend the SERB Sponsored National Seminar on AI for Health Care Innovation & Management (2023).

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