Earning Criteria

• The earner has completed the miniproject associated with the python for data science module, scoring at least 90%. They used Python and its libraries to clean and process JSON encoded data related to social interactions. They then analyzed this data to determine how participants were connected to each other.
• The earner has completed two miniprojects associated with the essential data tools module, scoring at least 90%. They use the Pandas library in Python to organize and process data from Excel, csv, and JSON files related to colleges and their communities. They have extracted insights about college prices, faculty salaries, and how colleges compare.
• The earner has completed two miniprojects about SQL. They have connected to local and remote databases, retrieved data, and performed analysis on customer behavior data using SQL. They have combined data from many tables and used complex queries to extract insights about customer purchases and ad viewing.
• The earner has completed two miniprojects associated with the practical machine learning module. They have used Scikit-learn to build regression models to predict housing sale prices, and classification models to predict whether cell phone customers will renew their contract. In both cases they have used feature engineering techniques and constructed pipelines to improve models performance.
• The earner has completed a capstone project to the satisfaction of TDI's instructors. The capstone project requires use of real-world data to provide insight into a practical problem. They used modern data analysis techniques to prepare data that they visualized in Tableau, creating interactive dashboards. These dashboards provide their target audience with a clear view into the problem and aid them in solving it.
• Earner attended courses from The Data Incubator, 21001 N Tatum Blvd Ste 1630 #642, Phoenix, AZ 85050, (480) 515-1411, thedataincubator.com, admissions@thedataincubator.com