Explore data literacy's role in personal life, society, and knowledge production. Learn to navigate data-driven technologies ethically.
Explore data literacy's role in personal life, society, and knowledge production. Learn to navigate data-driven technologies ethically.
This course examines data literacy from three crucial perspectives: data in personal life, data in society, and data in knowledge production. It aims to expand learners' skills in identifying, understanding, and interpreting the roles of digital technologies in daily life. The curriculum helps participants discern when data-driven technologies add value to people's lives and when they potentially exploit vulnerabilities or deplete common resources. Through a combination of lectures, readings, and interactive assignments, students develop a deeper understanding of how data-driven technologies shape knowledge production and how they can be realigned with human needs and values. The course covers topics such as user tracking, personal data management, the attention economy, the impact of networked data on truth and democracy, and the role of data in modern knowledge creation, including AI research and computational social science.
4.7
(95 ratings)
7,914 already enrolled
Instructors:
English
21 languages available
What you'll learn
Understand the concept of data literacy and its importance in modern society
Analyze personal data collection practices and their implications for privacy
Evaluate the impact of data-driven technologies on information dissemination and democracy
Explore the role of algorithms and AI in shaping social interactions and decision-making
Examine the application of big data and computational methods in knowledge production
Assess the ethical considerations in data use and algorithmic decision-making
Skills you'll gain
This course includes:
2.85 Hours PreRecorded video
8 quizzes,1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This course provides a comprehensive exploration of data literacy in the modern world, examining its impact on personal life, society, and knowledge production. It begins by investigating personal data management and digital privacy, helping learners understand the extent and implications of data collection in their daily lives. The curriculum then expands to explore how networked data and algorithms shape our worldview, discussing topics such as the attention economy, digital journalism, and the spread of information (and misinformation) in the digital age. The final section delves into data-driven knowledge production, covering cutting-edge topics like AI research, computational social science, and machine learning applications in various fields, including education and environmental monitoring. Throughout the course, participants are encouraged to think critically about the ethical implications of data use and to develop a nuanced understanding of how data-driven technologies can be harnessed for societal benefit while mitigating potential risks.
Your Life as Data
Module 1 · 3 Hours to complete
Networked Data, Truth and Democracy
Module 2 · 3 Hours to complete
Data-driven Knowledge Production
Module 3 · 4 Hours to complete
Fee Structure
Payment options
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Instructors
Leading Expert in Machine Learning at the University of Copenhagen
Christian Igel is a professor at the Department of Computer Science (DIKU) and serves as the director of the SCIENCE AI Centre at the University of Copenhagen. He studied Computer Science at the Technical University of Dortmund, Germany, earning his Doctoral degree from Bielefeld University in 2002 and his Habilitation from Ruhr-University Bochum in 2010. Before joining DIKU, he was a W1 professor for Optimization of Adaptive Systems at the Institut für Neuroinformatik, Ruhr-University Bochum, from 2003 to 2010. Appointed as a professor with special duties in machine learning at DIKU in 2010, he became a full professor in 2014. Igel is a fellow of the European Lab for Learning and Intelligent Systems (ELLIS) and serves as an editor for several journals, including the German Journal on Artificial Intelligence (KI) and the Evolutionary Computation Journal (ECJ). His research interests include deep neural networks, kernel-based methods, evolution strategies for optimization, reinforcement learning, and applying machine learning to achieve sustainable development goals.
Leader in Digital Education at the University of Copenhagen
Professor Morten Misfeldt is a prominent figure at the University of Copenhagen, where he serves as the leader of the Center for Digital Education within the Department of Science Education and the Department of Computer Science. His research focuses on the intersection of digitalization in teaching and learning, particularly within mathematics education. Professor Misfeldt has published extensively on topics such as game-based learning, learning analytics, and the impact of digital tools on mathematical thinking. Recently, he has explored the digitalization of educational infrastructure and the interplay between technology education and mathematics education. His work aims to enhance teaching practices through innovative digital solutions, contributing significantly to the advancement of educational methodologies in mathematics.
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4.7 course rating
95 ratings
Frequently asked questions
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