Data Scientist Associate

DS101 is a 60-minute exam where you'll choose either R or Python to work through the questions. This exam assesses your abilities to use R or Python for exploratory analysis and statistical experimentation. To successfully pass this exam, you should be able to:

• Calculate metrics to effectively report characteristics of data and relationships between features
• Create data visualizations in Python or R to demonstrate the characteristics of data
• Create data visualizations in Python or R to represent the relationships between features
• Describe statistical concepts that underpin hypothesis testing and experimentation (i.e., statistical distributions, power analysis, parameter estimation and confidence intervals)
• Apply sampling methods to data
• Implement methods for performing statistical tests

DS102 is a 60-minute exam where you'll choose either R or Python to answer questions about data management, modeling, and programming for data science. To successfully pass this exam, you should be able to:

• Perform standard data import, joining, and aggregation tasks
• Perform standard cleaning tasks to prepare data for analysis
• Assess data quality and perform validation tasks
• Prepare data for modeling by implementing relevant transformations
• Implement standard modeling approaches for supervised learning problems
• Use suitable methods to assess the performance of a model
• Implement approaches for unsupervised learning problems
• Use common programming constructs to write repeatable production quality code for analysis (i.e., functions, control flow, loops and iterations)