diff --git a/data/chapters_meetup.json b/data/chapters_meetup.json
index 9b23183..cee60c1 100644
--- a/data/chapters_meetup.json
+++ b/data/chapters_meetup.json
@@ -1194,7 +1194,7 @@
     "country_acronym": "co",
     "state": "",
     "city": "Medellín",
-    "members": 1153,
+    "members": 1154,
     "lat": 6.25,
     "lon": -75.59,
     "timezone": "America/Bogota"
@@ -1602,7 +1602,7 @@
     "country_acronym": "us",
     "state": "MO",
     "city": "Saint Louis",
-    "members": 1722,
+    "members": 1724,
     "lat": 38.63,
     "lon": -90.19,
     "timezone": "America/Chicago"
@@ -1614,7 +1614,7 @@
     "country_acronym": "tw",
     "state": "",
     "city": "Taipei",
-    "members": 2528,
+    "members": 2529,
     "lat": 25.02,
     "lon": 121.45,
     "timezone": "Asia/Taipei"
@@ -2730,7 +2730,7 @@
     "country_acronym": "us",
     "state": "WA",
     "city": "Seattle",
-    "members": 1368,
+    "members": 1369,
     "lat": 47.61,
     "lon": -122.33,
     "timezone": "America/Los_Angeles"
diff --git a/data/events.json b/data/events.json
index 570ed59..6a636f9 100644
--- a/data/events.json
+++ b/data/events.json
@@ -45,7 +45,7 @@
     "id": "305281979",
     "group_urlname": "rladies-taipei",
     "title": "Global AI Bootcamp 2025 in Taipei",
-    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>Global AI Bootcamp 2025 in Taipei<\/h6><p><i class='fa fa-users'><\/i>&emsp;6<\/p><p class='text-truncate'>2025 年即將是 AI 大爆發的一年，不但各種超強人工智慧會橫空出世，更多衍生出來的軟體應用，可能會無孔不入地入侵你的生活！\n為了讓大家無痛接軌跟上這班車，本活動邀請了微軟的專家們，用 2 小時的時間，讓你追上這個 AI 畫圖和對話機器人的時代，快速站上 AI 浪潮！\n\n本活動適合各種程度的群眾參加，不論你是否懂 AI，是否會寫程式，只要你有興趣了解最新的 AI 議題，都歡迎你來與我們分享及交流！\n\n**[注意事項]**\n*R-Ladies Taipei 是女性為主的社群，不過，為了慶祝久違的實體活動，此次活動特地開放男性參加。但是與此同時，我們還是希望參加的男性受眾盡量與女性朋友協同參加。*\n\n**[活動場地]**\n台北大學\n臺北市中山區民生東路三段67號 教學大樓 9樓\n\n**[活動網站]**\n\n**[議程]**\n\n**[講者與主持簡介]**\n\n*Kristen Chan*\n台灣微軟 Microsoft Technical Trainer / R-Ladies Taipei 現任負責人\n喜歡學任何新鮮有趣的東西，期望能貢獻自己的能力運用資料解決問題。\n\n*Kui-Ming Chen (Benjamin)*\nChimes AI 技術顧問 / Microsoft MVP\n致力於用資料科學解決各個領域的疑難雜症，舉凡股票、期貨、廣告、生技醫療和環保，都有實務處理的經驗。除了資料科學以外，近年也投入參與 IoT 的開發與專利申請，開始進入跨足 AI、IoT、雲端的三棲狀態。\n\n*Gene Liang*\n商智雲 協理 / Microsoft MVP / 科技 Youtuber\n對人工智慧和低代碼開發投入實務應用有極大熱忱，積極吸收資訊產業對新技術的發展。除此之外，我也是一個喜歡跑步和閱讀科幻小說的人，喜歡在閒暇時間裡放鬆心情。我相信，通過不斷學習和挑戰自我，我能夠不斷創造自己的價值。\n\n*孫玉峰*\n台灣角川數據架構師\n在多個產業開發各種資料產品，包含推薦系統以及廣告數據平台（DMP／CDP），近年來的公開演講以及實務上則專注在資料工程與 MLOps 的建立，期望讓數據驅動（Data-Driven）的觀念帶動各個產業領域的創新。《數位時代》專欄作家、微軟最有價值專家（MVP）以及 Taiwan R User Group（常態活動 MLDM Monday 主辦單位）的共同主持人（Co-organizer）。\n\n*Ning Chen*\nMicrosoft MVP / R-Ladies Taipei Organizer / D4SG Manager\n參與推動data for social good資料英雄計畫 [http://d4sg.org/fellowship/](http://d4sg.org/fellowship/)，此計劃運作六年，推動公益性質組織及公部門的大量營運數據發揮價值。歷年來，已經有超過40個政府機關及NGO透過這個計畫更加深入了解資料價值，輔導過社會及環保相關議題的資料分析案，2017\\~2022連續五年在AI類別取得微軟MVP榮譽，活耀於AI、機器學習相關研究、社群、競賽活動並且多場海內外AI相關專題演講經驗。帶領AI團隊與台北市社會救助科拿到聯發科「智在家鄉」百萬首獎。<\/p><center><a href='https://www.meetup.com/rladies-taipei/events/305281979' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
+    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>Global AI Bootcamp 2025 in Taipei<\/h6><p><i class='fa fa-users'><\/i>&emsp;7<\/p><p class='text-truncate'>2025 年即將是 AI 大爆發的一年，不但各種超強人工智慧會橫空出世，更多衍生出來的軟體應用，可能會無孔不入地入侵你的生活！\n為了讓大家無痛接軌跟上這班車，本活動邀請了微軟的專家們，用 2 小時的時間，讓你追上這個 AI 畫圖和對話機器人的時代，快速站上 AI 浪潮！\n\n本活動適合各種程度的群眾參加，不論你是否懂 AI，是否會寫程式，只要你有興趣了解最新的 AI 議題，都歡迎你來與我們分享及交流！\n\n**[注意事項]**\n*R-Ladies Taipei 是女性為主的社群，不過，為了慶祝久違的實體活動，此次活動特地開放男性參加。但是與此同時，我們還是希望參加的男性受眾盡量與女性朋友協同參加。*\n\n**[活動場地]**\n台北大學\n臺北市中山區民生東路三段67號 教學大樓 9樓\n\n**[活動網站]**\n\n**[議程]**\n\n**[講者與主持簡介]**\n\n*Kristen Chan*\n台灣微軟 Microsoft Technical Trainer / R-Ladies Taipei 現任負責人\n喜歡學任何新鮮有趣的東西，期望能貢獻自己的能力運用資料解決問題。\n\n*Kui-Ming Chen (Benjamin)*\nChimes AI 技術顧問 / Microsoft MVP\n致力於用資料科學解決各個領域的疑難雜症，舉凡股票、期貨、廣告、生技醫療和環保，都有實務處理的經驗。除了資料科學以外，近年也投入參與 IoT 的開發與專利申請，開始進入跨足 AI、IoT、雲端的三棲狀態。\n\n*Gene Liang*\n商智雲 協理 / Microsoft MVP / 科技 Youtuber\n對人工智慧和低代碼開發投入實務應用有極大熱忱，積極吸收資訊產業對新技術的發展。除此之外，我也是一個喜歡跑步和閱讀科幻小說的人，喜歡在閒暇時間裡放鬆心情。我相信，通過不斷學習和挑戰自我，我能夠不斷創造自己的價值。\n\n*孫玉峰*\n台灣角川數據架構師\n在多個產業開發各種資料產品，包含推薦系統以及廣告數據平台（DMP／CDP），近年來的公開演講以及實務上則專注在資料工程與 MLOps 的建立，期望讓數據驅動（Data-Driven）的觀念帶動各個產業領域的創新。《數位時代》專欄作家、微軟最有價值專家（MVP）以及 Taiwan R User Group（常態活動 MLDM Monday 主辦單位）的共同主持人（Co-organizer）。\n\n*Ning Chen*\nMicrosoft MVP / R-Ladies Taipei Organizer / D4SG Manager\n參與推動data for social good資料英雄計畫 [http://d4sg.org/fellowship/](http://d4sg.org/fellowship/)，此計劃運作六年，推動公益性質組織及公部門的大量營運數據發揮價值。歷年來，已經有超過40個政府機關及NGO透過這個計畫更加深入了解資料價值，輔導過社會及環保相關議題的資料分析案，2017\\~2022連續五年在AI類別取得微軟MVP榮譽，活耀於AI、機器學習相關研究、社群、競賽活動並且多場海內外AI相關專題演講經驗。帶領AI團隊與台北市社會救助科拿到聯發科「智在家鄉」百萬首獎。<\/p><center><a href='https://www.meetup.com/rladies-taipei/events/305281979' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
     "start": "2025-03-15 13:30:08",
     "end": "2025-03-15 15:30:08",
     "date": "2025-03-15",
@@ -115,7 +115,7 @@
     "id": "305437426",
     "group_urlname": "rladies-st-louis",
     "title": "R vs Python for Data Analytics: A Comparative Walkthrough",
-    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>R vs Python for Data Analytics: A Comparative Walkthrough<\/h6><p><i class='fa fa-users'><\/i>&emsp;31<\/p><p class='text-truncate'>Ebuwa Evbuoma-Fike is a Senior Data Scientist with over 8 years of experience driving impactful data-driven solutions in healthcare and civic tech. Passionate about improving health outcomes, especially for underserved communities, she excels in developing and implementing sophisticated data analyses, from complex machine learning models to insightful reporting.\n\nShe has a proven track record of success in both the public and private sectors, collaborating seamlessly with cross-functional teams to address critical challenges and optimize operational efficiency. Her expertise spans data engineering, predictive modeling, and translating complex technical insights into actionable strategies for leadership.\n\nThis workshop will introduce R users to the Python ecosystem for everyday data analysis tasks. We'll explore core Python concepts and libraries, comparing them to familiar R tools. You'll learn how to perform common data analysis operations in Python, such as data manipulation, exploratory data analysis (EDA), and data visualization. This hands-on session will provide you with a solid foundation to start using Python for your routine data analysis needs, expanding your analytical toolkit.<\/p><center><a href='https://www.meetup.com/rladies-st-louis/events/305437426' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
+    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>R vs Python for Data Analytics: A Comparative Walkthrough<\/h6><p><i class='fa fa-users'><\/i>&emsp;33<\/p><p class='text-truncate'>Ebuwa Evbuoma-Fike is a Senior Data Scientist with over 8 years of experience driving impactful data-driven solutions in healthcare and civic tech. Passionate about improving health outcomes, especially for underserved communities, she excels in developing and implementing sophisticated data analyses, from complex machine learning models to insightful reporting.\n\nShe has a proven track record of success in both the public and private sectors, collaborating seamlessly with cross-functional teams to address critical challenges and optimize operational efficiency. Her expertise spans data engineering, predictive modeling, and translating complex technical insights into actionable strategies for leadership.\n\nThis workshop will introduce R users to the Python ecosystem for everyday data analysis tasks. We'll explore core Python concepts and libraries, comparing them to familiar R tools. You'll learn how to perform common data analysis operations in Python, such as data manipulation, exploratory data analysis (EDA), and data visualization. This hands-on session will provide you with a solid foundation to start using Python for your routine data analysis needs, expanding your analytical toolkit.<\/p><center><a href='https://www.meetup.com/rladies-st-louis/events/305437426' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
     "start": "2025-02-08 10:00:06",
     "end": "2025-02-08 12:00:06",
     "date": "2025-02-08",
@@ -171,7 +171,7 @@
     "id": "304199693",
     "group_urlname": "rladies-philly",
     "title": "Lunch&Learn: {targets} with Irena Papst",
-    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>Lunch&Learn: {targets} with Irena Papst<\/h6><p><i class='fa fa-users'><\/i>&emsp;34<\/p><p class='text-truncate'>Do you ever find yourself starting with a simple analysis script only to end up wrangling a thousand line behemoth? Are you sick of wasting time re-running long scripts from start to finish, just to make sure everything is up-to-date? Are you (haphazardly?) saving objects to file because they take a long time to generate? There’s got to be a better way!\n\nEnter {targets}, an R package used to build reproducible, efficient, and scalable pipelines. {targets} can free you from many common analysis management tasks so that you can focus on the analysis itself. In this session, I’ll introduce the {targets} package and share how I’ve used it to streamline my work. I'll also highlight some tips and tricks that I've learned from my experience with the package over the last two years.<\/p><center><a href='https://www.meetup.com/rladies-philly/events/304199693' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
+    "body": "<h6 class='entry-title mt-2' style='font-size: 1.5em !important';>Lunch&Learn: {targets} with Irena Papst<\/h6><p><i class='fa fa-users'><\/i>&emsp;33<\/p><p class='text-truncate'>Do you ever find yourself starting with a simple analysis script only to end up wrangling a thousand line behemoth? Are you sick of wasting time re-running long scripts from start to finish, just to make sure everything is up-to-date? Are you (haphazardly?) saving objects to file because they take a long time to generate? There’s got to be a better way!\n\nEnter {targets}, an R package used to build reproducible, efficient, and scalable pipelines. {targets} can free you from many common analysis management tasks so that you can focus on the analysis itself. In this session, I’ll introduce the {targets} package and share how I’ve used it to streamline my work. I'll also highlight some tips and tricks that I've learned from my experience with the package over the last two years.<\/p><center><a href='https://www.meetup.com/rladies-philly/events/304199693' target='_blank'><button class='btn btn-primary'>Event page<\/button><\/center><\/a>",
     "start": "2025-01-22 12:00:05",
     "end": "2025-01-22 13:00:05",
     "date": "2025-01-22",
diff --git a/data/events_updated.json b/data/events_updated.json
index 26ab391..3bad733 100644
--- a/data/events_updated.json
+++ b/data/events_updated.json
@@ -1,6 +1,6 @@
 [
   {
-    "date": "2025-01-12 12:10:51",
+    "date": "2025-01-13 00:35:31",
     "n_events_past": 3943
   }
 ]