UNITAR Online Catalogue

CIFAL Honolulu - Data Lifecycle Course

Population

Date limite
Type
Course
Emplacement
Honolulu, Hawaii, United States of America
Date
to
Durée
116 Days
Zone du programme
Decentralize Cooperation Programme
Site internet
https://unitar.org/about/offices-training-centres-around-world/cifal-honolulu
Prix
0.00 $US
Personne de référence de l'évenement
cifa@unitar.org
Partenariat
CIFAL Honolulu
Chaminade University

Arrière plan

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).

Objectifs de l'événement

'-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

Objectifs d'apprentissage

'-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

Contenu et structure

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

Méthodologie

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.

Audience visée

College Students