Machine Learning Data Analytics

HS MD SUFIYAAN ZAFAR

+91-959******* *****************@*****.*** Github LinkedIn

PROFILE

Motivated and enthusiastic AI & ML engineering student with hands-on experience in machine learning projects, data analytics, and full-stack development. Proficient in Java, Python, SQL, and Power BI, with a keen interest in building scalable, data-driven, and innovative tech solutions. Skilled in analyzing complex datasets to derive actionable insights and improve decision-making. A quick learner with strong problem-solving and time management abilities, eager to contribute to impactful projects in dynamic environments. EDUCATION

Bachelor of Engineering (B.E.) in Computer Science and Engineering – Artificial Intelligence & Machine Learning Vidyavardhaka College of Engineering, Mysore, Karnataka Duration: 2021-2025

CGPA: 8.2/10

Specialized in AI & ML with coursework in Machine Learning, Data Structures, Object-Oriented Programming, and Data Analysis

Developed academic and personal projects using Python, Java, and ML frameworks SKILLS

Technical: Python, Java, OOPS in Java, SQL, Data Analytics, Data Visualization, Computer Vision, Machine Learning, Deep Learning, OpenCV, PyTorch, HTML, CSS, React Js

Tools: Tableau, Power BI, VS Code, Microsoft Office suite CERTIFICATIONS

Google Cloud Associate Cloud Engineer Track – Google

Google Data Analytics Specialization – Google

Java Programming – Great Learning

Mastering Python – Infosys Springboard

Big Data Analytics – Coursera

Fundamentals of UI/UX Design – Coursera

Strategy Formulation and Data Visualization – IIT Madras EXPERIENCE

CIS Intern – Cognizant Technology Solutions, Chennai Duration: [Jan, 2025 – May, 2025]

Gained practical experience in enterprise IT infrastructure, including Azure Cloud, VMware, Windows Server, and Linux system administration.

Developed skills in identity and access management using Active Directory, along with deploying and managing collaboration tools like Outlook, Teams, and SharePoint.

Built a foundational understanding of ITIL practices, cloud provisioning, automation, and virtualization technologies. AI Intern – Bolt IoT (Inventrom Private Limited))

Duration: [Apr, 2024 – May, 2024]

Designed and implemented AI/ML-based solutions using Python for real-world problem statements

Developed and deployed projects including a Personal Health Assistant and a Custom Chatbot, focusing on natural language understanding and user interaction

PROJECTS

Final Year Project: Correlation between Parkinson’s Disease and Type 2 Diabetes 11/24-04/25

Explored the relationship between Parkinson’s disease and Type 2 diabetes using data analysis and machine learning.

Identified and analysed 4 significant case scenarios showing possible links between the two diseases.

Provided insights into shared risk factors to help improve early diagnosis and treatment strategies.

Aimed to contribute to better understanding of comorbidity and improve healthcare outcomes. Sign Language Detection using Machine Learning 07/24 – 08/24

Developed a real-time sign language detection system to recognize hand gestures and translate them into text, aiding communication for the hearing-impaired

Tools/Technologies: Python, Mediapipe, OpenCV, LSTM (TensorFlow/Keras)

Achieved accurate, real-time gesture recognition; improved accessibility and user interaction with low-latency prediction

Winner Prediction using Machine Learning 12/23 –01/24

Built a classification model to predict the winner of IPL matches based on historical data, team stats, and venue conditions

Tools/Technologies: Python, Pandas, Scikit-learn, Matplotlib

Reached ~80% accuracy on test data; demonstrated ability to preprocess data and apply ML algorithms effectively AI-Powered Personalized Health Recommender 04/24-05/24

Developed an AI system to provide personalized health tips and recommendations based on user inputs such as age, gender, symptoms, and lifestyle habits

Tools/Technologies: Python, Pandas, Scikit-learn, Natural Language Processing (NLP), Flask

Enabled intelligent health advice generation using rule-based filtering and machine learning classification; improved user engagement by delivering relevant, data-driven health insights in real-time Food Delivery and Gym Login Websites 01/23-01/23

Designed responsive front-end interfaces for a food delivery system and a gym member login portal

Tools/Technologies: HTML, CSS, JavaScript

Showcased clean UI/UX design practices and mobile-first development principles ACHIEVEMENTS

Winner of Model Making Competition on Data Structures and Algorithms (DSA) in Java, demonstrating in-depth technical knowledge and creativity in presenting core CS concepts.

Winner of Model Making Competition on Operating Systems, recognizing excellence in visualizing and presenting complex OS concepts effectively.

Runner-up in CodeHunt Programming Competition, showcasing strong problem-solving skills and algorithmic thinking.

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