Hey! I’m Gurpreet — a data enthusiast, problem solver, and tech explorer with a Master’s in Computer Engineering from the University of Windsor and hands-on experience transforming complex data into actionable insights.
At Alpha Tickets, I designed intuitive Power BI dashboards and crafted data models that brought clarity to complex sales and customer behavior data. I built and maintained robust data pipelines using Python and Airflow, connecting multiple platforms to streamline analytics. By optimizing databases and implementing governance tools like data dictionaries, I ensured data was not only fast but also reliable for decision-making across the organization.
In this role, I applied machine learning models to solve real-world forecasting challenges, helping the business better align inventory with demand. My work involved analyzing production processes, uncovering inefficiencies, and turning insights into action. I developed dynamic dashboards and conducted customer behavior analyses that informed strategic planning, from operations to marketing.
During my co-op, I focused on automating and enhancing the way data was handled—from collection to reporting. I created clean, efficient pipelines and interactive dashboards that supported marketing and client retention efforts. It was a hands-on experience that sharpened my technical foundation and sparked my passion for using data to drive meaningful outcomes.
Key Highlights: Deep Learning, Computational Methods & Modeling for Engineers, Automotive Sensor Systems, Connected Autonomous Vehicles, Engineering Mathematics, Engineering Project Management
Key Highlights: Programming and Data Structures, Databases, Microprocessors & Microcontrollers, Industrial Automation, Mathematics & Calculus, Circuit Theory & Network Analysis
Certified in PL-300. Skilled in building data-rich dashboards with DAX and Power Query.
Experienced in distributed data processing, ETL, and ML workflows using Databricks.
Advanced use for analytics, automation, and financial modeling with Power Query.
Proficient in writing optimized queries and managing relational databases.
Used for data transformation, automation, and building machine learning models.
Skilled in using Azure (AZ-900 certified), AWS, and GCP for cloud-based analytics and infrastructure.
Developed low-code business apps integrated with SharePoint and Power BI.
Certified in DP-100. Built models for forecasting and classification using Scikit-learn and Azure ML.
Exploring GPT, Hugging Face, and LLaMA 3 for building AI-powered solutions and insights.
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Competitor Sales Analysis
Developed an interactive Power BI dashboard to analyze sales and market share for a fictional manufacturer, Sintec. Leveraged Power Query for data transformation, DAX for performance comparisons, and AI visualizations to uncover key revenue drivers. Delivered a branded, stakeholder-ready report focused on product-level insights and competitor benchmarking.
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Analyzing Healthcare Data
Acted as a data consultant for HealthStat to analyze real-world hospital performance data. Built a data model, applied DAX for in-depth analysis, and used Key Influencer visuals to identify drivers of patient length of stay and discharge costs. Delivered a 3-page branded report with actionable insights for healthcare stakeholders.
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Inventory Analysis
Conducted ABC classification and inventory turnover analysis for a fictional retailer, WarmeHands Inc. Cleaned and modeled data using Power Query, and applied intermediate DAX to uncover insights on product performance. Identified high-priority items for inventory optimization and purchasing strategy improvements through dynamic visuals and KPIs.
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Netflix Trends
Built an interactive Power BI dashboard to explore Netflix’s library of 8,800+ titles. Users can filter by year, genre, rating, and content type to uncover trends and insights. The dashboard features a clickable world map for global production analysis and dynamic visuals for comparing movies vs. TV shows. A great example of turning static data into an engaging, real-time exploration tool.
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Analyzing Car Reviews with LLMs
Designed a smart chatbot prototype for a car dealership using Hugging Face’s pre-trained LLMs. The app performs sentiment classification (80% accuracy), multilingual support through translation (BLEU: 0.60), question answering, and summarization. Built entirely without fine-tuning, the chatbot intelligently analyzes customer reviews to enhance service quality for both agents and users.
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Pending Credit Card Approvals
Built a machine learning model to automate credit card approval decisions using a dataset from the UCI Machine Learning Repository. Cleaned and imputed missing values, encoded categorical data, and applied feature scaling. Trained a logistic regression classifier and fine-tuned it with GridSearchCV for optimal hyperparameters. Achieved an accuracy of ~79%, streamlining the manual evaluation process used by banks.
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Real-Time Object Detection using OpenCV
Built a real-time object and traffic light detection system for autonomous vehicles using YOLO and OpenCV. Achieved high FPS with multithreading, enabling accurate detection on 4K streams. Improved perception and decision-making for navigation, safety, and traffic management.
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Adaptive Cruise Control System
+1 (437)559-4149
gurpreetsiingh545@gmail.com
Ontario, Canada
Category - Web Application
trying-gurpreet Singh
