(Please note that as of March 14th, this certification was renamed from the Data Scientist Professional Certification to the Data Scientist Certification. More information on the changes can be found here.)
Certification Requirements
What to expect on the exams
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
DS201 is a 60-minute exam that assesses your data management, programming, and modeling skills in R or Python, and data management skills using SQL. To successfully pass this exam, you should be able to:
- Perform data extraction, joining and aggregation tasks in SQL
- Perform cleaning tasks to prepare data for analysis in SQL
- Assess data quality and perform validation tasks in SQL
- Perform standard data import, joining, and aggregation tasks using R or Python
- Perform standard cleaning tasks to prepare data for analysis using R or Python
- Assess data quality and perform validation tasks using R or Python
- Collect data from non-standard formats using R or Python
- 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)
- Demonstrate best practices in production code including version control, testing and package development (i.e., version control, package building)
What to expect on the practical exam
The final step in this certification is a practical exam. The practical exam assesses your skills in data visualization and communication. You'll review a business problem, select and create appropriate visualizations, and give a relevant summary of what you have found to the defined audience. You'll need to record your presentation and submit it via the certification portal. You can find more information on how we grade the Data Scientist practical exam in the full rubric.
To pass the practical exam, you'll need to be able to:
- Present data concepts to small, diverse audiences
- Effectively employ data visualization to support my findings
- Frame, convey, and summarize stories using data
- Employ multiple tactics (written and verbal) to communicate to business leaders
If you have questions or feedback related to certification, please submit your inquiry here.