This credential earner has developed career-ready skills in data engineering and created a portfolio from labs and projects. They demonstrated abilities to perform key tasks in roles requiring skills in Python, NoSQL databases, relational databases (RDBMS), SQL, as well as familiarity with Hadoop and Spark, and creating data warehouses utilizing business intelligence tools. The learner brings together these skills to implement various data repositories and pipelines to create a data platform.
Additional DetailsSkills
Earning Criteria
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Receive the Data Engineering Professional Certificate from Coursera with a minimum passing grade of 70%.
Standards
The learning outcomes and skills acquired can be recognized as modules in subsequent educational courses, with a recommendation for recognition at EQF levels 5 and 6 for their designated ECTS credits. This certificate includes a workload of approximately 217 learning hours, providing a comprehensive learning experience.
Higher Education Institutions within the European Higher Education Area are obligated to recognize prior learning and non-formal learning experience, accepting up to a certain amount from non-university modules, provided there are no major differences in learning outcomes. Specific acceptance and applicability may vary by institution.
