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Career Advancement Programme in Data Science for Public Health (Advanced)

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The Career Advancement Programme in Data Science for Public Health is an advanced certificate programme comprising 20 units, designed to equip learners with the essential skills required for a successful career in the rapidly growing field of data science for public health. This programme is crucial in today's healthcare landscape, as it addresses the growing demand for data-driven insights to improve public health outcomes and inform evidence-based policy-making.

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์ด ๊ณผ์ •์— ๋Œ€ํ•ด

With the increasing availability of healthcare data, there is a pressing need for professionals who can collect, analyze, and interpret complex data to drive decision-making. This programme will equip learners with the skills to: Collect, manage, and analyze large datasets; Apply data visualization techniques to communicate findings; Develop predictive models and machine learning algorithms; Integrate data science with public health principles and practices; Design and implement data-driven solutions for public health challenges; Communicate complex data insights to diverse stakeholders. This programme is ideal for professionals looking to advance their careers in data science, public health, or epidemiology, or those seeking to transition to a career in data-driven public health.

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์–ด๋””์„œ๋“  ํ•™์Šต

๊ณต์œ  ๊ฐ€๋Šฅํ•œ ์ธ์ฆ์„œ

LinkedIn ํ”„๋กœํ•„์— ์ถ”๊ฐ€

์™„๋ฃŒ๊นŒ์ง€ 2๊ฐœ์›”

์ฃผ 2-3์‹œ๊ฐ„

์–ธ์ œ๋“  ์‹œ์ž‘

๋Œ€๊ธฐ ๊ธฐ๊ฐ„ ์—†์Œ

๊ณผ์ • ์„ธ๋ถ€์‚ฌํ•ญ

  • Introduction to Data Science for Public Health
  • Foundations of Data Analytics in Public Health
  • Data Visualization for Public Health Decision Making
  • Machine Learning for Predictive Modeling in Public Health
  • Introduction to Python Programming for Data Science
  • Working with Databases in Public Health
  • Data Mining for Public Health
  • Statistical Inference for Public Health Data
  • Introduction to R Programming for Data Science
  • Data Storytelling for Public Health Communication
  • Real-World Applications of Data Science in Public Health
  • Big Data Analytics for Public Health
  • Healthcare Data Standards and Interoperability
  • Advanced Data Visualization for Public Health
  • Deep Learning for Public Health Applications
  • Machine Learning for Healthcare
  • Data Science for Public Health Policy
  • Best Practices for Data Science in Public Health
  • Data Science Project Development for Public Health
  • Effective Communication of Data Science Results in Public Health

๊ฒฝ๋ ฅ ๊ฒฝ๋กœ

As you progress in your career, it's essential to stay ahead of the curve and adapt to the evolving landscape of public health data science.

The following roles are key to your success and growth.

Data Scientist (20%) - Design and develop data-driven solutions to drive informed decision-making in public health.

Statistician (18%) - Apply statistical techniques to extract insights from complex data sets and inform public health policy.

Researcher (15%) - Conduct research to identify trends, patterns, and correlations in public health data to inform evidence-based practice.

Analyst (47%) - Analyze and interpret complex data sets to identify areas of improvement and inform public health policy and practice.

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

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ํš๋“ํ•  ๊ธฐ์ˆ 

Data manipulation Statistical analysis Programmatic thinking Domain expertise

์ฝ”์Šค ์ˆ˜๊ฐ•๋ฃŒ

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์ƒ์„ธํ•œ ์ฝ”์Šค ์ •๋ณด๋ฅผ ๋ณด๋‚ด๋“œ๋ฆฌ๊ฒ ์Šต๋‹ˆ๋‹ค

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๊ฒฝ๋ ฅ ์ธ์ฆ์„œ ํš๋“

์ƒ˜ํ”Œ ์ธ์ฆ์„œ ๋ฐฐ๊ฒฝ
CAREER ADVANCEMENT PROGRAMME IN DATA SCIENCE FOR PUBLIC HEALTH (ADVANCED)
์—๊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”.
์ƒˆ ๋“ฑ๋ก
4.8

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