Aspiring Data Analyst | Microsoft-Certified
Computer Science graduate passionate about turning data into meaningful insights. Ready to drive data-driven decisions with Python, SQL, Power BI, and Excel expertise.
Driven by curiosity and a passion for solving real-world problems through data
As a Computer Science graduate from FISAT, I've built a strong foundation in data analysis, AI, and full-stack development. During my academic journey, I led the development of an AI-based proctoring system using face authentication and gaze tracking, and built service-based web platforms with .NET and MySQL.
My certifications from Microsoft, LinkedIn, and HackerRank in data analytics, Azure AI, Python, and SQL reflect my commitment to mastering the tools that drive today's data-driven decisions. As Vice Chair of IEEE FISAT SB, I developed leadership skills while managing teams and delivering impactful technical initiatives.
Showcasing my technical skills through real-world applications
Developed an intelligent proctoring solution using face authentication and gaze tracking technologies to ensure exam integrity. Implemented machine learning algorithms for real-time monitoring and anomaly detection.
Created a comprehensive home maintenance services website where homeowners can choose various services from registered providers. Features include user registration, service booking, and provider management.
Built a music player using linked lists data structure for efficient track management. Features include playlist creation, track navigation, and library management with intuitive user interface.
Developed a digital clock application using Java Swing and AWT packages. Displays real-time system time with customizable interface and multiple time format options.
Comprehensive analysis of Netflix's content library using advanced analytics, machine learning, and NLP techniques. Built content-based recommendation engine with 94.7% accuracy predictive models, sentiment analysis, and interactive visualizations uncovering content strategy patterns across 6,000+ titles and 42+ genres.
Comprehensive data science project analyzing Spotify music data using advanced statistical methods, machine learning, and clustering techniques. Built popularity prediction models with R² > 0.83 accuracy, implemented K-means clustering for musical style identification, and performed temporal analysis across 156,608+ tracks from 33,375+ artists spanning 1921-2020, revealing key insights into music evolution and popularity factors.
Produced educational video content using DaVinci Resolve during internship at Opengrad Foundation. Enhanced learner engagement through data-driven content optimization and cross-functional collaboration.
Industry-recognized credentials demonstrating expertise in data analytics and technology
Microsoft
Demonstrated foundational knowledge of machine learning and artificial intelligence concepts and related Microsoft Azure services.
LinkedIn Learning
Comprehensive certification covering data collection, analysis, visualization, and interpretation using industry-standard tools and methodologies.
HackerRank
Validated proficiency in Python programming fundamentals, data structures, algorithms, and problem-solving techniques.
HackerRank
Certified in SQL fundamentals including database querying, data manipulation, joins, and database design principles.
Ready to collaborate and create data-driven solutions
I'm excited to kick-start my career in Data or Business Analysis. Let's connect for full-time opportunities, mentorship, and collaborations in the tech and analytics space.