Assignments

Present your idea for an AI tutor:

For your Spark programming project, you will explore a large, real-world public dataset using PySpark and transform complex data into actionable insights, culminating in professional visualizations. The goal is to simulate a practical data analytics workflow akin to those found in industry: you will acquire and preprocess the data at scale using Spark, define and compute three significant business or analytical insights, and present each insight through well-crafted static plots. This project challenges you not only to harness distributed computing for big data processing, but also to bridge the gap between large-scale computation and clear, impactful communication of findings, preparing your analyses as compelling visual reports ready for BI or decision-making audiences. Through this assignment, you’ll develop the core skills of data wrangling, scalable analysis, and effective storytelling with data—making your technical results accessible and persuasive to both technical and non-technical stakeholders.

This programming project challenges to develop a comprehensive computer vision system for analyzing urban traffic signs from real-world street scene imagery. Students will apply classical computer vision techniques, feature extraction methods, traditional machine learning classifiers, and modern deep learning approaches to build a robust traffic sign detection and recognition pipeline. The project uses the Mapillary Traffic Sign Dataset (https://www.mapillary.com/dataset/trafficsign) , which contains over 100,000 high-resolution images from diverse global locations with varying weather conditions, lighting, viewpoints, and camera sensors—making it an ideal testbed for advanced computer vision methods.

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