This credential earner has demonstrated proficiency in applying different analytical techniques by analyzing real-world datasets, creating visualizations & interactive dashboards, and presenting reports to share findings of data analysis, and is now equipped with skills for an entry-level role in data analytics. The earner has successfully completed 9 courses in Data Analytics and gained hands-on experience with data analysis tools, including Excel, SQL, Databases, Python, JupyterLab and Cognos.
Additional DetailsSkills
Earning Criteria
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Pass all graded assessments and earn a course certificate for each of the 9 courses in the Professional Certificate.
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 151 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.
Endorsements
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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 12 college credits. For more information about ACE Learning Evaluations, visit www.acenet.edu. -
American Council on Education
3 semester hours in introduction to data analytics in the lower-division undergraduate category -
American Council on Education
3 semester hours in introduction to SQL programming in the lower-division undergraduate category -
American Council on Education
3 semester hours in introduction to Python programming in the lower-division undergraduate category -
American Council on Education
3 semester hours in advanced topics in data analytics in the upper-division undergraduate category