5.0
Intermediate
8h
Updated 3 months ago
Solving the Traveling Salesperson Problem in Python
Learn about solving the Traveling Salesperson Problem using Python. Explore geospatial data, clustering, network graphs, and Docker to optimize routes and create dynamic, interactive visualizations.
Solving complex computational problems is a resource-demanding task. The traveling salesperson problem (TSP) is one such problem, which is an NP-hard problem. In the era of data science, data-centric approaches have evolved to be a good choice to approximate the solutions.
In this course, you’ll dive into the fascinating realm of geospatial data manipulation, distance calculation, clustering, network graphs, and Docker containerization, all tied together to optimize the challenging TSP. You’ll first grasp the intricacies of manipulating geospatial data and plotting it. Next, you’ll delve into clustering sales data, enhancing your ability to make data-driven decisions and visualize the data mining results in interactive dashboards.
By the end of this course, you’ll be skilled in tackling TSP effectively and creating geospatial data visualizations. You’ll also be well-equipped to scale route optimization, data analysis, and cloud deployment.
Solving complex computational problems is a resource-demanding task. The traveling salesperson problem (TSP) is one such problem...Show More
WHAT YOU'LL LEARN
An understanding of geospatial data manipulation, plotting, and their application to optimizing routes
Working knowledge of distance calculation techniques, their role in solving the traveling salesperson problem (TSP), and alternate methods to solve TSP
Hands-on experience clustering sales data and finding patterns
Ability to create interactive dashboards showcasing optimal routes and data mining insights
An understanding of geospatial data manipulation, plotting, and their application to optimizing routes
Show more
Content
1.
What the Traveling Salesperson Problem Is About
5 Lessons
Get familiar with the TSP, its challenges, practical applications, and geospatial data intricacies.
2.
Preprocessing of Traveling Salesperson Data
6 Lessons
Unpack the core of data preprocessing, analysis, manipulation, and visualization for the Traveling Salesperson Problem.
3.
Solving the Traveling Salesperson Problem
12 Lessons
Master the steps to comprehensively calculate and optimize routes for the Traveling Salesperson Problem using various distance metrics and algorithms.
4.
Traveling Salesperson Data Mining
8 Lessons
Grasp the fundamentals of network graphs, data clustering, KPI enhancement, data enrichment, and interactive storytelling techniques.
5.
Building the Traveling Salesperson Dashboard
2 Lessons
Solve problems in building interactive dashboards for visualizing TSP using Python’s Dash library.
6.
Scalability
2 Lessons
Tackle large-scale TSP using heuristic methods and cloud platforms for enhanced efficiency.
7.
Conclusion
1 Lessons
Practice using skills in geospatial data, visualization, clustering, and application deployment.
8.
Appendix
9 Lessons
Learn how to use Python tools and platforms for TSP development and deployment.
Certificate of Completion
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