Intro to Data Analytics
Students will learn the technical skills needed to clean messy data and audit charts for accuracy and quality. They will practice choosing the best analytical methods to solve real-world problems based on the specific needs of an organization. Finally, students will become experts at interpreting complex graphs and case studies to turn data into clear, evidence-based stories that help people make smart decisions.
- Type Validation
- Level Foundational
- Time Weeks
- Cost Paid
Skills
Earning Criteria
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Complete DATA 1113 Introduction to Data Analytics - Course provides an overview of the different types of data analytics and how they are used in different real-world settings. Students will learn how to perform basic data cleaning and the concepts of how to evaluate the quality of basic data visualization for the information they convey. Students/Learners will select the data analytics method that should be used in the real-world scenario.
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Students will transition from understanding broad theory to applying specific analytical techniques and here are the relevant skills students will gain upon successful completion of this micro credential paced course:
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Technical Skills: Execute basic data cleaning and visualization audits
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Analytical Skills: Interpret complex graphical data and case-based narratives.
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Application Skills: Match analytical methods to specific real-world organizational needs.
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Data Preparation and Quality Check: Students will be able to fix errors in messy datasets and judge whether a chart is showing information accurately or in a misleading way.
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Strategic Method Selection: Students will know how to look at a real-life problem and pick the specific type of data analysis needed to find the best solution.
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Evidence-Based Interpretation: Students will be able to read complex case studies and graphs to explain the "story" behind the numbers and what actions should be taken next.
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DATA 1113 provides an overview of the different types of data analytics and how they are used in different real-world settings. Students will learn how to perform basic data cleaning and the concepts of how to evaluate the quality of basic data visualization for the information they convey. Students/Learners will select the data analytics method that should be used in the real-world scenario, and they will learn how to read and interpret case studies, charts, and graphs.