Tipo
Course
Plazo

CIFAL Honolulu - Data Lifecycle Course

Ubicación
Honolulu, Hawaii, United States of America
Fecha
-
Duración
116 Days
Área del programa
Decentralize Cooperation Programme
Precio
0,00 US$
Correo Electrónico del Centro de Coordinación del Evento
cifa@unitar.org
Colaboración
CIFAL Honolulu
Chaminade University
Inscripción
Open-registration event
Tipo de aprendizaje
Face-to-Face
Idioma(s)
English
Pilar
Personas
Objetivos del evento

'-Identify and describe the stages of the data lifecycle.  -Connect the stages of data lifecycle to real-world use cases  -Conceptualize data science theory and practice as decision science, using the UN SDG to illustrate use cases for data-driven decision support  -Analyze decision support use cases as example of data science processes and methods that are stages of the Data Lifecycle  -Identify data forms and structures across domains of human knowledge including quantitative and social sciences, and the arts.  -Explain opportunities and concerns surrounding the application of AI and ML to decision support  -Describe and implement best practices in data visualization and storytelling for diverse audiences

Antecedentes

This course will use case studies presented by Chaminade and external experts to illustrate the application of the data lifecycle to major global challenges, framed around the United Nations Sustainable Development Goals (SDG, e.g., Climate Action, Health Equity, Gender Equity, Justice).

Objetivos del aprendizaje

'-Identify and describe the stages of the data lifecycle.  -Connect the stages of data lifecycle to real-world use cases  -Conceptualize data science theory and practice as decision science, using the UN SDG to illustrate use cases for data-driven decision support  -Analyze decision support use cases as example of data science processes and methods that are stages of the Data Lifecycle  -Identify data forms and structures across domains of human knowledge including quantitative and social sciences, and the arts.  -Explain opportunities and concerns surrounding the application of AI and ML to decision support  -Describe and implement best practices in data visualization and storytelling for diverse audiences

Contenido y estructura

This course will include lectures, discussions, assignments, and a project that could be used for future classes and investigation 

Metodología

The course will examine a broad range of types, forms and structures of data that humans use to transmit information and that can be analyzed and visualized to gain knowledge. We will address the role of AI and Machine Learning in decision support. Finally, we will engage with our data scientist identities as storytellers, exploring best practices and case studies in visualization.

Público objetivo

College Students

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