2026 NCCU PS × ESSEX SUMMER SCHOOL
APPLICATION INFOR MATION
Essex Summer School in Social Science Data Analysis is an internationally renowned training program in social science research methods. Since 1967, it has connected social science research communities around the world. Taught by instructors from leading research institutions, the program offers rigorous and intensive methodological training, helping graduate students strengthen the skills needed for their theses, postdoctoral research, and other academic projects
ESSEX Website：https://essexsummerschool.com/
Application closing date:
|
Period |
Dates |
|
Pre-sessional 1 |
2026/06/29 (Mon) – 2026/07/03 (Fri) |
|
Session 1 |
2026/07/06 (Mon) – 2026/07/17 (Fri) |
|
Pre-sessional 2 |
2026/07/13 (Mon) – 2026/07/17 (Fri) |
|
Session 2 |
2026/07/20 (Mon) – 2026/07/31 (Fri) |
|
Session 3 |
2026/08/03 (Mon) – 2026/08/14 (Fri) |
|
PRE-SESSIONAL 1（6/29–7/3） |
|
|
10:00–13:30 |
R Programming for the Social Sciences／Python for Social Scientists |
|
14:15–16:45 |
Linear Algebra／Functions & Calculus |
|
SESSION 1（7/6–7/17） |
|
|
10:00–13:30 |
Quantitative Methods in R、Longitudinal & Panel Data、Categorical Data Analysis、Survey Design、Intro & Quantitative Text Analysis、Discourse Analysis、Qualitative Data Analysis、Mixed Methods、Fieldwork Preparation |
|
14:15–17:45 |
Research Design、Data Science in R、Data Visualization with R、Social Statistics using Stata、Applied Causal Inference、Measurement & Model Estimation |
|
10:00–17:45 |
Qualitative Interviewing（7/6–10） |
|
PRE-SESSIONAL 2（7/13–7/17） |
|
|
10:00–13:30 |
R Programming for the Social Sciences |
|
14:15–16:45 |
Linear Algebra／Functions & Calculus |
|
SESSION TWO（7/20–7/31） |
|
|
10:00–13:30 |
AI-Enhanced Research Design、Generative AI、Python Programming、Quantitative Data Analysis with R、Bayesian Analysis、Geospatial Data & Spatial Analysis、Spatial Econometrics、Machine Learning for Treatment Effects、Quantitative Text Analysis、Machine Learning for Social Scientists、Applied Discourse Analysis |
|
14:15–17:45 |
Game Theory、Agent-Based Models、Web Scraping & Data Management、Longitudinal Data Analysis、Time Series & Panel Data、Causal Inference & Experiments、IRT & Scaling Methods、Multimodal Language Data、Qualitative Methods |
|
10:00–17:45 |
Ethnographic Methods（7/20–24） |
|
SESSION THREE（8/3–8/14） |
|
|
10:00–13:30 |
Regression、Multilevel Models、Bayesian Latent Variable Models、SEM using R、LLM-Assisted Text Analysis、Discourse Theory |
|
14:15–17:45 |
Survey Experimental Design、Causal Inference for Policy Evaluation、Tree-based Machine Learning |
|
10:00–17:45 |
Deep Learning for Text & Vision（8/3–7） |
2026 政大政治 × 艾塞克斯大學 暑期資料分析學程
申請資訊
Essex Summer School in Social Science Data Analysis 是國際知名的社會科學方法訓練課程，自 1967 年起持續連結全球社會科學研究社群。課程由來自世界頂尖研究機構的師資授課，提供嚴謹且密集的研究方法訓練，協助研究生強化論文、博士後研究或其他學術計畫所需的方法能力。每年約有來自 40 多個國家、超過 500 位社會科學領域學生參與，形成重要的國際學術交流與專業網絡。
請參閱ESSEX官方網站：https://essexsummerschool.com/
申請截止日期：
|
期程 |
時間 |
|
預備課程1 |
2026/06/29 (一) – 2026/07/03 (五) |
|
第一梯次課程 |
2026/07/06 (一) – 2026/07/17 (五) |
|
預備課程2 |
2026/07/13 (一) – 2026/07/17 (五) |
|
第二梯次課程 |
2026/07/20 (一) – 2026/07/31 (五) |
|
第三梯次課程 |
2026/08/03 (一) – 2026/08/14 (五) |
本系已簽署合作，凡本系推薦學生報名各式課程，均享專屬學費減免優惠。
官網費率資訊：https://essexsummerschool.com/summer-school-facts/fee-structure/
|
預備課程1（6/29–7/3） |
|
|
10:00–13:30 |
R Programming for the Social Sciences／Python for Social Scientists |
|
14:15–16:45 |
Linear Algebra／Functions & Calculus |
|
第一梯次課程（7/6–7/17） |
|
|
10:00–13:30 |
Quantitative Methods in R、Longitudinal & Panel Data、Categorical Data Analysis、Survey Design、Intro & Quantitative Text Analysis、Discourse Analysis、Qualitative Data Analysis、Mixed Methods、Fieldwork Preparation |
|
14:15–17:45 |
Research Design、Data Science in R、Data Visualization with R、Social Statistics using Stata、Applied Causal Inference、Measurement & Model Estimation |
|
10:00–17:45 |
Qualitative Interviewing（7/6–10） |
|
預備課程2（7/13–7/17） |
|
|
10:00–13:30 |
R Programming for the Social Sciences |
|
14:15–16:45 |
Linear Algebra／Functions & Calculus |
|
第二梯次課程（7/20–7/31） |
|
|
10:00–13:30 |
AI-Enhanced Research Design、Generative AI、Python Programming、Quantitative Data Analysis with R、Bayesian Analysis、Geospatial Data & Spatial Analysis、Spatial Econometrics、Machine Learning for Treatment Effects、Quantitative Text Analysis、Machine Learning for Social Scientists、Applied Discourse Analysis |
|
14:15–17:45 |
Game Theory、Agent-Based Models、Web Scraping & Data Management、Longitudinal Data Analysis、Time Series & Panel Data、Causal Inference & Experiments、IRT & Scaling Methods、Multimodal Language Data、Qualitative Methods |
|
10:00–17:45 |
Ethnographic Methods（7/20–24） |
|
第三梯次課程（8/3–8/14） |
|
|
10:00–13:30 |
Regression、Multilevel Models、Bayesian Latent Variable Models、SEM using R、LLM-Assisted Text Analysis、Discourse Theory |
|
14:15–17:45 |
Survey Experimental Design、Causal Inference for Policy Evaluation、Tree-based Machine Learning |
|
10:00–17:45 |
Deep Learning for Text & Vision（8/3–7） |
