SQL for Healthcare

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 10 lectures (3h 43m) | 2.71 GB

Let’s Learn SQL and Healthcare Analytics Concepts Together

SQL for Healthcare looks to provide students a single course to learn SQL and United States Healthcare concepts together. Through the use of MySQL (an open source and free tool) we will explore various use cases like patient volumes, emergency room throughput, and procedures to learn new SQL and healthcare analytics skills. I will be taking an approach of presenting healthcare topics briefly before diving into working examples using SQL. My intent is to help us apply technical concepts of the SQL language while at the same time learning new healthcare knowledge. Following each lecture, there will be an assignment for students to really apply and grow beyond what we cover over video content. I have found this approach really helps with long term retainment of skills. This course is great for anyone new to healthcare and/or SQL and is meant to help others jump start a career in healthcare analytics.

This course was created by me – Mark Connolly, MEng. I’m currently a Business Intelligence Lead and co-lead for the virtual Tableau Healthcare User Group. I have almost 10 years of experience in the healthcare analytics space in general. I have used SQL heavily in my most recent role to answer many healthcare clinical analytics questions.

Beyond my experience working directly with SQL, I have also developed internal Tableau training programs and provided 100’s (if not 1000’s) of hours of training support to analysts both at his current organization and externally. I am also the creator for the strongly reviewed Tableau for Healthcare course on Udemy.

Please note that this course utilizes training data and is not reflective of any current or past performance or clinical data for any patient, health system, insurance provider, or any other entity. All data is fake and made available for educational purposes only.

What you’ll learn

• Using SQL to answer questions in healthcare
• Reading SQL
• Writing SQL
• Navigating a data enviornment