Training
This section contains resources such as how-to guides, talks, and Jupyter notebooks that aim to enhance skills in data engineering and related fields.
How-To Guides
Getting Started with ETL Using Python
This guide walks through the basics of building ETL pipelines using Python, covering key libraries and best practices.
Read Guide →Data Visualization Techniques
Learn about different techniques for effective data visualization, including charts, graphs, and dashboards.
Read Guide →Recent Talks
Harnessing Data for Educational Insights
A talk exploring how data analytics can transform educational practices and improve student outcomes, presented at the Academic Data Conference.
Watch Talk →Challenges in Data Integration for Higher Education
Discussing the unique challenges faced in integrating data from multiple academic systems at the Annual Data Engineering Workshop.
Watch Talk →Notebooks
Exploratory Data Analysis with Pandas
This Jupyter notebook explores data analysis techniques using the Pandas library, focusing on real-world datasets.
View Notebook →Machine Learning for Predictive Modeling
A comprehensive notebook that showcases machine learning techniques for predictive modeling, including model evaluation methods.
View Notebook →