黑料不打烊

Coding Ateliers

As part of CDSI, the聽Data Science Solutions Hub (DaS2H)聽offers Coding Ateliers to the entire 黑料不打烊 community, where you can drop-in during atelier hours with your laptop, work on your research project and, whenever you have a question, we would be happy to assist you on the spot. If your question turns out to be a bigger issue that we cannot solve instantly, we will advise you how to best proceed.

Overview:聽In this workshop you will learn how to efficiently find and extract census data and its geographical boundaries in R for the Canadian, the US and EU censuses.

At the end of this workshop, you will be able to
聽聽聽聽聽 路 find and extract data efficiently from the Canadian census
聽聽聽聽聽 路 find and extract data efficiently from the US census
聽聽聽聽聽 路 find and extract data efficiently from the Eurostat census
聽聽聽聽聽 路 extract geographic boundary files, combine them with census data and display them on a map

Maching Learning in Python - Unsupervised learning and model validation

翱惫别谤惫颈别飞:听This workshop will focus on unsupervised machine learning and model validation. Unsupervised machine learning is a powerful technique where the algorithm analyzes and clusters unlabeled datasets. This workshop will scratch the surface of this side of machine learning, introducing unsupervised learning using the k-means and DBSCAN algorithms. This session will explore the model validation process in the machine learning pipeline in more detail.

Overview: R is mostly known for its statistical methods on numbers. However, it is also capable of working efficiently with text and analysing it. In this workshop we will take a deep dive into how to work with text in R and introduce you to functions that allow you to even do text mining.
At the end of this workshop, you will be able to
聽 聽 路 manipulate strings efficiently
聽 聽 路 import text from multiple sources
聽 聽 路 lay the basis for working with regular expressions (regex)
聽 聽 路 do some text mining with the tidytext package

Overview: Many Generative Artificial Intelligence (GenAI) models now offer support in programming with different languages. In this workshop we will explore different models like OpenAI's ChatGPT, Anthropic's Claude and Microsoft's CoPilot in programming with R. We will discuss strengths and weaknesses, when and how to use GenAI using R.

Overview:

In this workshop, we will delve into the art of conducting Exploratory Data Analysis (EDA) on a given dataset. EDA encompasses a broad spectrum of critical data analysis components, which include, but are not restricted to, the following:

The internet is full of data that you can use for your analysis. As part of our data life cycle series, we will introduce you to efficiently retrieve data from the internet. We will look into downloading files, using APIs, web-scraping, and downloading feeds.

At the end of this workshop, you will be able to
聽聽 - use an API
聽聽 - understand ethical web-scraping (i.e. how to download data from a website)
聽聽 - understand how to work with RSS feeds