Machine learning for social impact
This course will be taught in English
Fees with academic credits:
*If you are in Colombia $4.024.000 COP
*If you are abroad USD $1118
For enrollment click here
Fees without academic credits:
*If you are in Colombia $3.733.000 COP
*If you are abroad USD $1040
For enrollment click here
Learn how to pay your payment here
Schedule: monday, tuesday, wednesday, thursday, friday18:00-20:45
*The schedules and modality (virtual or blended) of the courses are subject to modifications according to the provisions of the National and District Government for the management of COVID 19. The dates and times of the sessions can be consulted at mibanner.uniandes.edu.co
Machine Learning for Social Impact, a course oriented to Machine Learning applications for social problems, which would consider contextual, methodological and technical aspects in the design and deployment of Machine Learning solutions in these contexts.
Fechas:
08 de junio al 25 de junio de 2021
Curso finalizado
Duración:
32 horas
Inversión:
$ 4.024.000 hasta el 05 de junio de 2021
Modalidad:
Virtual
Lugar:
Modalidad Virtual
Este curso hace parte del portafolio de materias de pregrado y posgrado de la Universidad abiertas a todo público.
Al participar en este curso podrás vivir la experiencia Uniandina, acceder a contenidos de calidad, tomar clases con estudiantes regulares, acceder al sistema de bibliotecas de Uniandes y participar en las actividades culturales que esta Universidad te ofrece.
Profesores 
Rhema Vaithianathan is a Professor of Health Economics and Director of the Centre for Social Data Analytics (CSDA), a translational research centre located in the School of Social Sciences and Public Policy at AUT. She is also a Professor of Social Data Analytics at the Institute for Social Science Research at The University of Queensland (Australia), where she leads a second CSDA node. Rhema is recognised internationally for her work using data science for social good, and the implementation of machine learning tools in high stakes government systems such as child protection. She leads the international research team that developed, and continues to refine two active child protection predictive risk modelling tools: the Allegheny Family Screening Tool (Allegheny County, PA) and the Douglas County Decision Aide (Douglas County, CO). Additionally, she has developed a tool to assess homelessness in Allegheny County, aiding in prioritizing bed allocation within temporary housing. Rhema is currently leading the development of several new machine learning tools that will help Australian and US jurisdictions better address challenges they face in domains including health, education, housing, elder abuse and child protection.
Research interests span transfer learning, continual learning and human-algorithm collaboration in decision making contexts. Diana investigates fundamental aspects of these paradigms and lead the construction of decision-making support tools aligned with current advancements in these areas. Her applied experience includes a variety of projects in data science and machine learning, as well as teaching and tutoring in computer algorithms, programming and machine learning. Diana holds a PhD in Computer Science from the School of Computer Science, The University of Auckland, New Zealand.
Condiciones
Eventualmente la Universidad puede verse obligada, por causas de fuerza mayor a cambiar sus profesores o cancelar el programa. En este caso el participante podrá optar por la devolución de su dinero o reinvertirlo en otro curso de Educación Continua que se ofrezca en ese momento, asumiendo la diferencia si la hubiere.
La apertura y desarrollo del programa estará sujeto al número de inscritos. El Departamento/Facultad (Unidad académica que ofrece el curso) de la Universidad de los Andes se reserva el derecho de admisión dependiendo del perfil académico de los aspirantes.
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