The DS101 is a 2-hour exam where you'll choose either R or Python to work through the questions. Most candidates typically complete it in 45 minutes. 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

The DS102 is a 2-hour exam where you'll choose either R or Python to answer questions about data management, modeling, and programming for data science. Most candidates typically complete it in one hour. 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)