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 IBM Data Engineering Professional Certificate from Coursera.
Endorsements
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FIBAA
This credential has been successfully certified by the Foundation for International Business Administration Accreditation and is recommended for recognition of up to 8 ECTS credits. For more information about FIBAA, visit www.fibaa.org. -
American Council on Education
This credential has been successfully evaluated by the American Council on Education for college credit. It is recommended for a total of 15 college credits. For more information about ACE Learning Evaluations, visit www.acenet.edu. -
American Council on Education
3 semester hours in Introduction to Programming with Python in the lower-division undergraduate category -
American Council on Education
3 semester hours in Introduction to Relational Databases in the lower-division undergraduate category -
American Council on Education
3 semester hours in Advanced SQL Programming in the upper-division undergraduate category -
American Council on Education
3 semester hours in Practical Data Mining and Warehouse Implementation in the upper-division undergraduate category -
American Council on Education
3 semester hours in Data Engineering Techniques and Tools in the upper-division undergraduate category