An Introduction to the Teaching Reform of Data Science Courses in the Context of Big Data

\nIn the big data age, it’s imperative for data science courses to undergo transformation and embrace innovation. Building upon the foundation of existing data science education, we should introduce a big data-informed perspective for curriculum reform. This reform should encompass specific strategies and measures across various dimensions, including curriculum content, pedagogical approaches, theoretical instruction, and practical application scenarios. The goal of this curriculum overhaul is to foster an integration of modern statistical techniques with big data analytics, balancing theoretical knowledge with hands-on experience. It aims to develop students’ statistical acumen and their ability to manage complex datasets within the big data landscape. By doing so, it seeks to elevate students’ overall proficiency and empower them with the skills to apply contemporary mathematical and statistical methods to tackle realworld challenges effectively.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-12-13
DOI
https://doi.org/10.1051/shsconf/202420901012/pdf
Primary Topic
Statistics Education and Methodologies
Type
article
Field-Weighted Citation Impact
0.00
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article

An Introduction to the Teaching Reform of Data Science Courses in the Context of Big Data

Springer Link (Chiba Institute of Technology)
Statistics Education and Methodologies
article

An Introduction to the Teaching Reform of Data Science Courses in the Context of Big Data

article en

Abstract

\nIn the big data age, it’s imperative for data science courses to undergo transformation and embrace innovation. Building upon the foundation of existing data science education, we should introduce a big data-informed perspective for curriculum reform. This reform should encompass specific strategies and measures across various dimensions, including curriculum content, pedagogical approaches, theoretical instruction, and practical application scenarios. The goal of this curriculum overhaul is to foster an integration of modern statistical techniques with big data analytics, balancing theoretical knowledge with hands-on experience. It aims to develop students’ statistical acumen and their ability to manage complex datasets within the big data landscape. By doing so, it seeks to elevate students’ overall proficiency and empower them with the skills to apply contemporary mathematical and statistical methods to tackle realworld challenges effectively.\n

Springer Link (Chiba Institute of Technology)
Industry, innovation and infrastructure
Openalex Percentile: Top 71%
Statistics Education and Methodologies
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