I learned about:

• The applications of the SQL programming language in data science
• What distinguishes SQL from other languages (it is non-procedural)
• How R’s array-oriented syntax makes it easier to understand for people with a non-programming background
• The difference between data management, data integration and transformation, data visualization, code asset management, and development environments.
• Different frameworks and options for data science project needs