Welcome to our Data Science ACE course designed for intensive care medicine medical doctors who have little to no prior experience in data science.  

In today's intensive care units, data has become an indispensable asset for evidence-based decision making. The ability to analyse and interpret datasets has become essential for medical doctors to provide high-quality patient care, optimize treatment plans, and drive operational efficiency. 

To help critical care medical doctors make sense of data, understanding a data science project workflow is key. This workflow involves defining the problem, collecting and cleaning data, exploring and visualizing data, building models, and communicating results. In a clinical medicine setting, defining the problem might involve identifying a medical issue that needs to be solved or an opportunity for improvement in patient care. Collecting and cleaning data might involve accessing electronic medical records or medical devices and ensuring that the data is complete and accurate. Exploring and visualizing data might involve using tools like charts, graphs, or statistical analysis to identify patterns and trends. Building models might involve using machine learning algorithms to develop models that can predict patient outcomes or identify at-risk patients. Finally, communicating results might involve presenting findings to medical colleagues or hospital administrators in a way that is easy to understand and actionable. 

This course is specifically tailored to equip intensive care medical doctors with the fundamental skills and knowledge necessary to understand, analyse and interpret clinical data sets. Throughout the course, you will learn how to use data analysis tools and techniques, build models, and draw meaningful insights from data. 

Our course is designed to be practical and hands-on, with a simple example and a real-world example and case study from a critical care unit. By the end of the course, you will have a foundation in data science and be able to start applying these skills in your day-to-day work and have the skills and necessary knowledge to further your knowledge in data science.