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Inicio 4 June 2026 00:05
Fin 4 June 2026
Big Data and Education
Columbia University
17 Cursos
La Universidad de Columbia es una escuela de la Ivy League ubicada en Nueva York que proporciona una educación de clase mundial en una comunidad de aprendizaje diversa y vibrante.
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Resumen
Explore the transformative power of big data in the educational sector with our comprehensive course offered through edX at Columbia University. Embrace the opportunity to delve into the burgeoning field of educational data mining and learning analytics, tailored to augment educational effectiveness and foundational research on learning dynamics.
Through this meticulously designed course, participants will acquire proficiency in the paramount methods of educational data mining and learning analytics.
The curriculum is crafted to provide insights into the innovative methods fostered by the educational data mining, learning analytics, learning-at-scale, student modeling, and artificial intelligence communities.
Gain hands-on experience with prevalent data mining techniques specifically applied to educational data, mastering both the application and timing of these methods. Understand the strengths and limitations inherent to each method across diverse applications, enhancing your ability to apply these techniques effectively.
Dive into the practical application of these methods to answer pressing research questions within the realm of education, driving significant interventions and advancements in educational software and systems.
The course not only focuses on theoretical aspects but also on practical application, including learning how to employ these methods using Python or tools like RapidMiner.
An essential component of the course is the discussion around validity and generalizability, crucial for establishing the reliability and applicability of analysis results. Categories include Big Data Courses and Data Science Courses, positioning this course as an ideal choice for anyone looking to make a substantial impact in the educational field through the lens of big data.
Impartido por
Ryan Baker
