Category: Big Data Beginner

This course aims to explore the reproducibility of big data performance in modern cloud networks. The learning outcomes include understanding the impact of variability on cloud-based big data workloads, characterizing network variability, and providing guidelines to enhance the repeatability of experiments. The course teaches skills such as assessing performance in the cloud, measuring network variability,…

This course explores the future of big data-driven technology and design, focusing on machine learning advancements and the expansion of human knowledge. The teaching method involves a thrilling science talk presented by Kenneth Cukier. The intended audience includes individuals interested in technology, data science, machine learning, and the impact of big data on various fields.…

This course focuses on the importance of incorporating “thick data” – qualitative insights from individuals – alongside big data for making informed business decisions. The goal is to demystify big data and highlight its limitations, emphasizing the value of human-centric insights. The course teaches the skill of distinguishing between big data and thick data, and…

This course explores the challenges faced by whistleblowers in an era of widespread surveillance and big data. Participants will learn about the extent of surveillance by tech companies and governments, the risks whistleblowers face, and the legal implications of leaking information to the media. The course aims to raise awareness about privacy issues and the…

This course explores how big data and machine learning are revolutionizing risk management. The learning outcomes include understanding the limitations of human bias in risk analysis, the role of algorithms in mitigating bias, and the potential of machine learning in uncovering new trends and correlations. The course teaches skills such as analyzing high-frequency data, utilizing…

This course aims to teach learners how to use machine learning methods to hunt for anomalies in HTTP responses and identify malicious infrastructure, specifically command and control (C&C) servers. The course covers feature extraction methods for analyzing HTTP response headers, advantages and disadvantages of different machine learning techniques, and the importance of identifying C&C servers…

This course aims to educate learners on the importance of securing and protecting data in Big Data projects. The learning outcomes include understanding the differences between Big Data and traditional data, recognizing data security and privacy challenges, and implementing best practices and technical controls for securing data. The course covers topics such as the history…

This course aims to teach learners about the intersection of big data and cyber security through the concept of adversarial data mining. By the end of the course, students will be able to understand the challenges and opportunities in leveraging big data for cyber security purposes. The course covers skills such as identifying potential threats…

This course aims to teach learners how to advance internet security research using big data and graph databases. The course covers topics such as utilizing graph databases, working with different data sources, developing prototypes, creating a research timeline, and building confidence in research outcomes. The teaching method involves presenting real-world examples and discussing research development…

This course explores the potential of data-driven intelligence in addressing global crises such as war, food shortages, and energy crises. The course discusses the role of software solutions in tackling complex problems and features insights from a leader in data analytics. The intended audience for this course includes individuals interested in the intersection of technology,…