Certification Requirements
DataCamp's Data Scientist Associate Certification is awarded to individuals who successfully complete two exams (DS101 and DS102) and one practical exam (DS501P).
What to expect on the exams
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)
What to expect on the practical exam DS501P
The final step in this certification is a practical exam. The practical exam assesses your skills in communication and data visualization. You'll review a business problem, select and create appropriate visualizations, fit and evaluate a model, and provide a written report of your summary. You can find more information on how we grade the Data Scientist practical exam in the full rubric.
To pass the case study, you'll need to be able to:
- Present data concepts to small, diverse audiences
- Leverage appropriate data visualization types to support your findings
If you have questions or feedback related to certification, please submit your inquiry here.