In this course, we will explore fundamental concepts involved in security and privacy of machine learning projects. Diving into the ethics behind these decisions, we will explore how to protect users from privacy violations while creating useful predictive models. We will also ask big questions about how businesses implement algorithms and how that affects user privacy and transparency now and in the future.
Este curso forma parte de Programa especializado: Ethics in the Age of AI
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Acerca de este Curso
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Fechas límite flexibles
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Certificado para compartir
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100 % en línea
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Curso 3 de 4 en
Nivel intermedio
Aprox. 6 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (europeo), Ruso (Russian), Inglés (English), Español (Spanish)
Habilidades que obtendrás
- Ethics
- Machine Learning
- Ethics Of Artificial Intelligence
- security
- Privacy
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 3 de 4 en
Nivel intermedio
Aprox. 6 horas para completar
Inglés (English)
Subtítulos: Francés (French), Portugués (europeo), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
LearnQuest
LearnQuest is the preferred training partner to the world’s leading companies, organizations, and government agencies. Our team boasts 20+ years of experience designing, developing and delivering a full suite industry-leading technology education classes and training solutions across the globe. Our trainers, equipped with expert industry experience and an unparalleled commitment to quality, facilitate classes that are offered in various delivery formats so our clients can obtain the training they need when and where they need it.
Programa - Qué aprenderás en este curso
2 horas para completar
Privacy and convenience vs big data
In Module 1, we are going to discuss what true anonymity and privacy mean in machine learning
2 horas para completar
5 videos (Total 19 minutos), 2 lecturas, 3 cuestionarios
2 horas para completar
Protecting Privacy: Theories and Methods
In Module 2, we are going to take a deeper look at dataset security. We will also look into methods to add privacy to existing and new datasets to protect those individuals in them
2 horas para completar
4 videos (Total 16 minutos), 2 lecturas, 3 cuestionarios
2 horas para completar
Building Transparent Models
In Module 3, we will discuss putting ethical, private models into practice. We will explore the explainable AI movement as well as tradeoffs for the teams putting together these algorithms
2 horas para completar
5 videos (Total 20 minutos), 1 lectura, 3 cuestionarios
Reseñas
Principales reseñas sobre ARTIFICIAL INTELLIGENCE PRIVACY AND CONVENIENCE
por CA12 de feb. de 2021
A good course on balancing between privacy and aggregate results. It tells how anonymization should be done. It did not cover enough the correlations between privacy and accuracy though
por YL22 de may. de 2021
The concepts were easier to grasp and a nice introduction into the complexities around algorithmic models and building ethical practices from the outset.
por SY2 de abr. de 2021
A relatively short but interesting course relating to privacy concerns around AI and ways to manage/improve models to address these concerns.
por AV16 de ene. de 2021
Extraordinary course! I've really enjoyed it and learned so much. Classes are very clear and concise. Thank you so much!
Acerca de Programa especializado: Ethics in the Age of AI
As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations. In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in security and privacy of machine learning projects. We'll finish with a study of 3 projects that will allow you to put your new skills into action.
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