Certificate in Fundamentals of Educational Data Analysis

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The Certificate in Fundamentals of Educational Data Analysis is a comprehensive course designed to equip learners with essential skills in educational data analysis. This program is crucial in today's data-driven world, where educators and administrators rely on data-informed decisions to improve student outcomes.

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The course covers key topics including data collection, cleaning, and visualization, as well as statistical analysis and interpretation. Learners will gain hands-on experience using popular data analysis tools and software, preparing them for real-world application. With a growing demand for data analysis skills in the education industry, this certificate course offers a valuable opportunity for career advancement. By completing this program, learners will demonstrate a mastery of essential skills and a commitment to staying at the forefront of educational data analysis, making them highly attractive candidates for employment and promotion.

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โ€ข Data Collection in Education
โ€ข Data Analysis Techniques for Education
โ€ข Introduction to Educational Data Analysis Software
โ€ข Statistical Methods for Educational Data Analysis
โ€ข Data Visualization in Education
โ€ข Data Interpretation and Presentation
โ€ข Assessment and Evaluation in Education
โ€ข Research Design and Methodology in Education
โ€ข Ethical Considerations in Educational Data Analysis
โ€ข Applying Data Analysis in Educational Decision Making

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This section features a 3D pie chart that highlights the job market trends in educational data analysis, focusing on four key roles: data analyst, data scientist, education technology specialist, and education data researcher. The chart, powered by Google Charts, adapts to various screen sizes with width set to 100% and a height of 400px. The transparent background and the lack of added background color ensure seamless integration into any webpage. The 3D pie chart offers a visually engaging way to compare the prevalence of these roles in the educational data analysis field. By having the chart data defined using the google.visualization.arrayToDataTable method and the is3D option set to true, the chart showcases the percentages in a 3D space, providing a more immersive experience for users. To ensure proper layout and spacing, inline CSS styles have been added. The Google Charts library is loaded correctly using the script tag, and the JavaScript code defines the chart data, options, and rendering logic within a
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