Type
Course
CIFAL Honolulu - Data Lifecycle Course
Location
Honolulu, Hawaii, United States of America
Date
-
Duration
116 Days
Programme Area
Decentralize Cooperation Programme
Partnership
CIFAL Honolulu
Chaminade University
Registration
Open-registration event
Mode of Delivery
Face-to-Face
Language(s)
English
Pillar
People
Event Objectives
'-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
Background
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).
Learning Objectives
'-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
Content and Structure
This course will include lectures, discussions, assignments, and a project that could be used for future classes and investigation
Methodology
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.
Targeted Audience
College Students
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