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Career Advancement Programme in Predictive Analytics for Education Policy

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Predictive Analytics for Education Policy: Advance your career. This programme equips education professionals with data analysis skills.

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์ด ๊ณผ์ •์— ๋Œ€ํ•ด

Learn statistical modeling and machine learning techniques. Forecasting student outcomes and improving policy are key focuses. Target audience: Education policymakers, researchers, and analysts. Gain practical experience through case studies and real-world datasets. Boost your employability in the rapidly growing field of educational data science. Transform educational systems with data-driven insights. Ready to make a difference? Explore the programme today!

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์–ด๋””์„œ๋“  ํ•™์Šต

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LinkedIn ํ”„๋กœํ•„์— ์ถ”๊ฐ€

์™„๋ฃŒ๊นŒ์ง€ 2๊ฐœ์›”

์ฃผ 2-3์‹œ๊ฐ„

์–ธ์ œ๋“  ์‹œ์ž‘

๋Œ€๊ธฐ ๊ธฐ๊ฐ„ ์—†์Œ

๊ณผ์ • ์„ธ๋ถ€์‚ฌํ•ญ

  • Introduction to Predictive Analytics and its Applications in Education
  • Data Wrangling and Preprocessing for Educational Datasets
  • Regression Modeling for Educational Outcomes Prediction
  • Classification Techniques for Student Performance Analysis
  • Clustering and Segmentation for Targeted Interventions
  • Causal Inference and Program Evaluation in Education
  • Data Visualization and Communication of Findings
  • Ethical Considerations in Educational Predictive Analytics
  • Case Studies: Successful Applications of Predictive Analytics in Education

๊ฒฝ๋ ฅ ๊ฒฝ๋กœ

Career Advancement Programme: Predictive Analytics for Education Policy (UK) Career Role Description Predictive Analytics Consultant (Education) Develop and implement predictive models to optimize education resource allocation and improve student outcomes.

Analyze large datasets for actionable insights.

Education Data Scientist Extract, clean, and analyze educational data using advanced statistical techniques and machine learning algorithms.

Build predictive models for policy recommendations.

Educational Policy Analyst (Predictive Modelling) Apply predictive analytics to inform evidence-based educational policy decisions.

Collaborate with policymakers and stakeholders to interpret findings and drive change.

Learning Analytics Specialist Leverage data to understand and improve student learning experiences.

Utilize predictive modelling to personalize learning pathways and identify at-risk students.

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์‚ฌ์ „ ๊ณต์‹ ์ž๊ฒฉ์ด ํ•„์š”ํ•˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค. ์ ‘๊ทผ์„ฑ์„ ์œ„ํ•ด ์„ค๊ณ„๋œ ๊ณผ์ •.

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์™œ ์‚ฌ๋žŒ๋“ค์ด ๊ฒฝ๋ ฅ์„ ์œ„ํ•ด ์šฐ๋ฆฌ๋ฅผ ์„ ํƒํ•˜๋Š”๊ฐ€

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์ด ๊ณผ์ •์˜ ๋น„์šฉ์„ ์ง€๋ถˆํ•˜๊ธฐ ์œ„ํ•ด ํšŒ์‚ฌ๋ฅผ ์œ„ํ•œ ์ฒญ๊ตฌ์„œ๋ฅผ ์š”์ฒญํ•˜์„ธ์š”.

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์ƒ˜ํ”Œ ์ธ์ฆ์„œ ๋ฐฐ๊ฒฝ
CAREER ADVANCEMENT PROGRAMME IN PREDICTIVE ANALYTICS FOR EDUCATION POLICY
์—๊ฒŒ ์ˆ˜์—ฌ๋จ
ํ•™์Šต์ž ์ด๋ฆ„
์—์„œ ํ”„๋กœ๊ทธ๋žจ์„ ์™„๋ฃŒํ•œ ์‚ฌ๋žŒ
London School of Planning and Management (LSPM)
์ˆ˜์—ฌ์ผ
05 May 2025
๋ธ”๋ก์ฒด์ธ ID: s-1-a-2-m-3-p-4-l-5-e
์ด ์ž๊ฒฉ์ฆ์„ LinkedIn ํ”„๋กœํ•„, ์ด๋ ฅ์„œ ๋˜๋Š” CV์— ์ถ”๊ฐ€ํ•˜์„ธ์š”. ์†Œ์…œ ๋ฏธ๋””์–ด์™€ ์„ฑ๊ณผ ํ‰๊ฐ€์—์„œ ๊ณต์œ ํ•˜์„ธ์š”.
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