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Aniket Hingane
Aniket Hingane

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Graph + AI : How I build Graph-Powered Journey Thr’ University’s Academic Universe

Topological Sort Algorithm | The AI That Knows Your Major

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Overview: Delve into the realm of topological sorting algorithms and witness how they streamline the course planning process, applicable not just to academia but also to real-world scenarios like network routing and supply chain management.

Why It Matters: For tech enthusiasts, curious minds, and learners alike, this article offers a creative application of tech concepts and provides insights into optimizing academic progression.

The Challenge: University course catalogs can be overwhelming, but fear not! here is a solution to decode the maze of prerequisites and dependencies.

The Solution: Imagine visualizing the entire academic universe, with each course as a node and prerequisites as edges. Using Python, NetworkX, and Neo4j, I've constructed a seamless pathway through the academic labyrinth.

The Execution: Dive into the technical details of data loading, graph creation, Neo4j interaction, topological sorting, and visualization using PyVis.

Key Achievements: Discover how we've identified foundational courses, revealed course dependencies, determined optimal sequences, and created visual representations to simplify course planning.

Closing Thoughts: As we conclude our journey through college class sorting, remember that technology is a powerful ally. Let's leverage it to make our lives easier and our academic journeys smoother.

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Struggling with slow API calls? Dan Mindru walks through how he used Sentry's new Trace View feature to shave off 22.3 seconds from an API call.

Get a practical walkthrough of how to identify bottlenecks, split tasks into multiple parallel tasks, identify slow AI model calls, and more.

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