Day 1 - Morning Session

This session will introduce AIS data. What it is, how it is structured, and how to access it via the UN Global Platform. Topics will include:

• Background information on AIS data (where it comes from, limitations, etc.)
• Walkthrough of the raw data (what columns mean, etc.)
• How to access AIS data from the UNGP
• Basic processing of raw AIS data
• Use cases for AIS data
• Workshop for morning session (30 minutes))

For this session, you will get:

Knowledge

• Comprehend what AIS data is and how it is structured.
• Understand the source, limitations, and potential of AIS data.

Skills

• Be able to identify and explain different columns in the raw AIS data.
• Know how to access AIS data from the UN Global Platform.

Competency

• Apply basic techniques to clean and transform raw AIS data.
• Gain hands-on experience through a 30-minute workshop, applying the learned knowledge and skills to real AIS data.

Day 1 - Afternoon Session

The second session will outline important concepts in structuring and organizing data science projects. Though important for any statistician, these topics are particularly important for working with AIS data. Topics will include:

• Version control (Git, etc.)
• Python/coding best practices (modular, flexible code, creating reusable libraries, etc.)
• Basic principles of extract, load, transform (ETL) pipelines.
• How to integrate these concepts to create automatically updateable, flexible, robust data products

Day 2 - Morning Session

This session will cover some basic shipping economics and operations concepts while exploring its dynamics as generated by real AIS data. The goal is to start building intuition on the strengths and limitations of AIS for generating statistics. The following three topics will cover the session

• Understanding Shipping Economics Through AIS Data
• Congestion Levels and Waiting Times Estimation
• Emissions Estimation for Regional and Local Areas

For this session, you will get:

Knowledge

• Understand how AIS data can be used to monitor key economic indicators and freight dynamics in the shipping industry.
• Understand how congestion and waiting times can lead to higher freight rates in shipping.
• Understand the "bottom-up" method for emissions estimation as adopted by the International Maritime Organization (IMO).
• Gain knowledge about how waiting times at ports can relate to higher emissions.

Skills

• Acquire the skills to manipulate AIS data to glean economic insights through a hands-on coding session.
• Learn how to use AIS data to estimate congestion levels and waiting times for a specific port.
• Learn the techniques for estimating emissions on a regional and local level using AIS data.
• Gain the skills needed to visualize emissions data effectively.

Competency

• Apply the knowledge and skills gained to conduct an analysis that extracts relevant economic insights from AIS data.
• Use AIS data to create an actionable model or tool that estimates congestion levels and waiting times for a selected port.
• Competently apply techniques to estimate emissions using AIS data, incorporating insights about the relationship between waiting times and emissions.
• Use data visualization skills to effectively communicate the emissions data and its implications.

Day 2 - Afternoon Session

The final session will feature an introduction to machine learning as well as a hands-on exercise in forecasting and nowcasting a country’s trade based on its port visits.