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Author: diego-init

docs/Courses.md

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 <u>__University of Toronto Summer 2024__</u>
 
+I assisted Prof. Amer Shalaby in developing and teaching a unique graduate-level course that focuses on the most advanced techniques used in public transit. This course covers topics such as AI models and advanced time series analysis. It emphasizes principles of data analysis, modeling, and visualization, with applications in transit reliability, equity, access to opportunities, demand forecasting, and real-time data analysis.
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 ### Course Description
 
 Transit agencies around the world witness a growing trend of data abundance and diversity, presenting opportunities to enhance transit system effectiveness but requiring specialized knowledge and experience with analytics for harnessing such data. Transportation agencies and companies overseeing other modes and emerging mobility services are faced with the same challenges. This course provides students with in-depth exposure to emerging data types, sources and standards for transit and other mobility systems . The course will cover a range of analytics for harnessing diverse data in a variety of  planning and management applications. While special focus will be given to transit applications, other mobility modes and services will be considered as appropriate.

docs/blog/posts/ai_agent_tutorial.md

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-# Getting Started with AI Agents
+# Getting Started with AI Agents - Part I
 
 It's hard to have a conversation about AI these days without bringing up tools like ChatGPT, DeepSeek, and the like, right? These tools are becoming key players in how we analyze and interact with public transport. Are you ready for this shift?