Data Scientist Professional

Certification Requirements

DataCamp’s Data Scientist Professional Certification is awarded to individuals who successfully complete two exams (DS 101 and DS 201) and one case study. You can find the comprehensive study guide here.
 

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 data management, exploratory analysis, and statistical experimentation. To successfully pass this exam, you should be able to:
 
  • Collect data from multiple sources and in a range of standard formats
  • Perform standard cleaning tasks to prepare data for analysis
  • Assess data quality and perform validation tasks
  • Collect data from non-standard formats (e.g. json) by modifying existing code
  • 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 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
  • 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 case study

The final step in this certification is a case study. The case study 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 case study in the full rubric.
To pass the case study, 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
     

How to prepare

Many certified individuals completed courses and tracks on DataCamp to prepare for the certification. We recommend that you complete either the Data Scientist with R or Data Scientist with Python career tracks, as well as the SQL Fundamentals skill track. You may want to enroll in the Data Communication Concepts course to prepare for the case study.
 

Skill Assessments

If you aren’t sure whether your skills are at the level required for certification, you might want to take the following skill assessments and see if your score is at or above the Professional Data Scientist level.
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