BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//PHIT4DC Up-Skilling District of Columbia public health professionals! - ECPv6.15.13.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.phit4dc.com
X-WR-CALDESC:Events for PHIT4DC Up-Skilling District of Columbia public health professionals!
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250220T170000
DTEND;TZID=America/New_York:20250220T200000
DTSTAMP:20260404T175205
CREATED:20241205T132346Z
LAST-MODIFIED:20250107T222015Z
UID:10000037-1740070800-1740081600@www.phit4dc.com
SUMMARY:Week 4 | Module 3A | Experimentation in Data Science (A/B Testing and Statistical Analyses) I
DESCRIPTION:Instructor: Ronald Doku\, Ph.D. \nThis topic covers the principles and applications of A/B testing\, a foundational technique for making data-driven decisions in healthcare\, business and various other industries. The session will focus on hypothesis testing\, including the formulation of null and alternate hypotheses\, and how they apply to experimental design. Attendees will learn about statistical concepts such as the central limit theorem\, the distribution of sample means\, and the importance of standard error in determining statistical significance. We will also explore how to calculate and interpret z-scores and t-scores\, with a focus on understanding effect size\, statistical power\, and their relationship to sample size. 
URL:https://www.phit4dc.com/event/week-4-module-3a-experimentation-in-data-science-a-b-testing-and-statistical-analyses-i-2/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250226T170000
DTEND;TZID=America/New_York:20250226T200000
DTSTAMP:20260404T175205
CREATED:20241205T132544Z
LAST-MODIFIED:20250107T222020Z
UID:10000038-1740589200-1740600000@www.phit4dc.com
SUMMARY:Week 5 | Module 3B | Experimentation in Data Science (A/B Testing and Statistical Analyses) II
DESCRIPTION:Instructor: Ronald Doku\, Ph.D. \nPart II will build on concepts discuss in Part I. We will go through examples of how to conduct an A/B test on a real-world use case\, covering all necessary processes from designing the experiment to interpreting the results.  Discuss situations when A/B testing doesn’t work. By the end of the session\, participants will be able to design and analyze A/B tests\, ensuring reliable conclusions from their experiments to support data driven decision making.
URL:https://www.phit4dc.com/event/week-5-module-3b-experimentation-in-data-science-a-b-testing-and-statistical-analyses-ii/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250227T170000
DTEND;TZID=America/New_York:20250227T200000
DTSTAMP:20260404T175205
CREATED:20241205T132921Z
LAST-MODIFIED:20250107T222026Z
UID:10000039-1740675600-1740686400@www.phit4dc.com
SUMMARY:Week 5 | Module 3B | Experimentation in Data Science (A/B Testing and Statistical Analyses) II
DESCRIPTION:Instructor: Ronald Doku\, Ph.D. \nPart II will build on concepts discuss in Part I. We will go through examples of how to conduct an A/B test on a real-world use case\, covering all necessary processes from designing the experiment to interpreting the results.  Discuss situations when A/B testing doesn’t work. By the end of the session\, participants will be able to design and analyze A/B tests\, ensuring reliable conclusions from their experiments to support data driven decision making.
URL:https://www.phit4dc.com/event/week-5-module-3b-experimentation-in-data-science-a-b-testing-and-statistical-analyses-ii-2/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250301
DTEND;VALUE=DATE:20250309
DTSTAMP:20260404T175205
CREATED:20241205T133347Z
LAST-MODIFIED:20250107T214051Z
UID:10000040-1740787200-1741478399@www.phit4dc.com
SUMMARY:Week 6 | Spring Break
DESCRIPTION:
URL:https://www.phit4dc.com/event/week-6-spring-break/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250312T170000
DTEND;TZID=America/New_York:20250312T200000
DTSTAMP:20260404T175205
CREATED:20241205T140359Z
LAST-MODIFIED:20250107T214044Z
UID:10000045-1741798800-1741809600@www.phit4dc.com
SUMMARY:Week 7 | Module 4 | Seminal Presentation on Current Development in Data Science
DESCRIPTION:Instructor: TBD. \nTopics to be determined.
URL:https://www.phit4dc.com/event/week-7-module-4-seminal-presentation-on-current-development-in-data-science/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250313T170000
DTEND;TZID=America/New_York:20250313T200000
DTSTAMP:20260404T175205
CREATED:20241205T140541Z
LAST-MODIFIED:20250107T214037Z
UID:10000046-1741885200-1741896000@www.phit4dc.com
SUMMARY:Week 7 | Module 4 | Seminal Presentation on Current Development in Data Science
DESCRIPTION:Instructor: TBD. \nTopics to be determined.
URL:https://www.phit4dc.com/event/week-7-module-4-seminal-presentation-on-current-development-in-data-science-2/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250319T170000
DTEND;TZID=America/New_York:20250319T200000
DTSTAMP:20260404T175205
CREATED:20241205T133938Z
LAST-MODIFIED:20250107T214031Z
UID:10000041-1742403600-1742414400@www.phit4dc.com
SUMMARY:Week 8 | Module 5 | Introduction to Machine Learning I 
DESCRIPTION:Instructor: Ebelechukwu Nwafor\, PhD \nThis two-part module delves into the core principles of machine learning. In Part I\, students will learn about supervised learning techniques\, covering linear regression\, classification\, and model evaluation metrics. They will explore foundational algorithms\, including decision trees\, support vector machines\, and k-nearest neighbors\, while focusing on applications in real-world scenarios.
URL:https://www.phit4dc.com/event/week-8-module-5-introduction-to-machine-learning-i/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250320T170000
DTEND;TZID=America/New_York:20250320T200000
DTSTAMP:20260404T175205
CREATED:20241205T134116Z
LAST-MODIFIED:20250107T214024Z
UID:10000042-1742490000-1742500800@www.phit4dc.com
SUMMARY:Week 8 | Module 5 | Introduction to Machine Learning I
DESCRIPTION:Instructor: Ebelechukwu Nwafor\, PhD \nThis two-part module delves into the core principles of machine learning. In Part I\, students will learn about supervised learning techniques\, covering linear regression\, classification\, and model evaluation metrics. They will explore foundational algorithms\, including decision trees\, support vector machines\, and k-nearest neighbors\, while focusing on applications in real-world scenarios.
URL:https://www.phit4dc.com/event/week8-module-5-introduction-to-machine-learning-i/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250321T170000
DTEND;TZID=America/New_York:20250321T200000
DTSTAMP:20260404T175205
CREATED:20241205T134345Z
LAST-MODIFIED:20250107T214018Z
UID:10000043-1742576400-1742587200@www.phit4dc.com
SUMMARY:Week 9 | Module 6 | Machine Learning II
DESCRIPTION:Instructor: Ebelechukwu Nwafor\, PhD \nPart II builds on these basics from Part I\, introducing unsupervised learning techniques such as clustering and dimensionality reduction. The module will also cover key concepts like overfitting\, and model selection. By the end\, students will understand both theoretical and practical aspects of machine learning\, with hands-on experience in building and evaluating models using tools like Scikit-Learn.
URL:https://www.phit4dc.com/event/week-9-module-6-machine-learning-ii/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250322T170000
DTEND;TZID=America/New_York:20250322T200000
DTSTAMP:20260404T175205
CREATED:20241205T134625Z
LAST-MODIFIED:20250107T214013Z
UID:10000044-1742662800-1742673600@www.phit4dc.com
SUMMARY:Week 9 | Module 6 | Machine Learning II
DESCRIPTION:Instructor:  Ebelechukwu Nwafor\, PhD \nPart II builds on these basics from Part I\, introducing unsupervised learning techniques such as clustering and dimensionality reduction. The module will also cover key concepts like overfitting\, and model selection. By the end\, students will understand both theoretical and practical aspects of machine learning\, with hands-on experience in building and evaluating models using tools like Scikit-Learn.
URL:https://www.phit4dc.com/event/week-9-module-6-machine-learning-ii-2/
CATEGORIES:VADSTI Training Program
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250721T173000
DTEND;TZID=America/New_York:20250905T184500
DTSTAMP:20260404T175205
CREATED:20250513T155453Z
LAST-MODIFIED:20250513T155745Z
UID:10000049-1753119000-1757097900@www.phit4dc.com
SUMMARY:Data for Decision-Making in Healthcare
DESCRIPTION:Transform Healthcare Decisions Through Data Literacy\nIn today’s healthcare environment\, the ability to interpret and leverage data is no longer optional—it’s essential. This 8-week intensive course equips professionals with practical data literacy skills that can be immediately applied to improve decision-making in clinical and operational settings. \nApply Today \nDuration\n8 weeks\n(July 21 – September 5) \nSchedule\nTuesdays and Thursdays\, 5:30 – 6:45 PM \nCourse Overview\nLed by Professor Michael Marcus\, this hands-on program bridges the gap between healthcare expertise and data fluency. Through a balanced combination of weekly lectures and laboratory sessions\, you’ll progress from understanding basic healthcare data types to creating professional dashboards that drive meaningful decisions. \nWhat makes this course unique:\n\nWork with real-world healthcare datasets relevant to your professional context\nDevelop practical skills in data visualization and dashboard creation\nLearn to communicate data insights effectively to various stakeholders\nGain exposure to google sheets and Gemini AI for simple\, AI-assisted formula generation\nComplete a personalized capstone project addressing a real healthcare challenge\n\nWho Should Attend\nThis course is designed for professionals who need to make or influence data-informed decisions\, including: \n\nAnyone seeking to enhance their data literacy\nClinical leaders and department managers\nHealthcare administrators and operations staff\nQuality improvement specialists\nHealth information professionals\n\nWhat You’ll Learn\n\nIdentify and work with different types of healthcare data (clinical\, operational\, financial)\nEvaluate data quality and relevance for healthcare decision-making\nCreate effective dashboards and visualizations that tell a compelling story\nDevelop data-informed recommendations that drive action\nPresent data insights with confidence and clarity\nUtilize Google Sheets and Gemini AI to enhance data analysis capabilities\n\nBy the end of this course\, you’ll possess the skills to transform raw healthcare data into actionable insights\, positioning yourself as a more valuable contributor to your organization’s success in an increasingly data-driven healthcare landscape. \nAll necessary software licenses will be provided\, including Excel and Power BI. Students should bring laptops to each session.
URL:https://www.phit4dc.com/event/data-for-decision-making-in-healthcare/
CATEGORIES:PHIT4DC Event
END:VEVENT
END:VCALENDAR