Inhalt: The revolution in data science has transformed, for better or worse, the way companies do business in the last few decades. But data science isn't just for capitalists. AI is one of the most important forces for change developed in the last century, and we've only begun to recognize its true power and potential. In Data for Good: Using Data Science in Nonprofits and NGOs, Martin Kemka examines how data science and machine learning can be used outside of the for-profit sector. He covers parameters for how data works to influence our world, how the data-for-good concept can be applied, how to determine the best problems to solve with data, and what tools are needed. Martin also provides real-world case studies and challenges to further illustrate the lessons. Umfang: 00:33:51
Inhalt: The main driver of the technological revolution isn't artificial intelligence or machine learning. It's data: data about people like us. So what rights do you have to your own data? What responsibilities do businesses and other institutions have in protecting and respecting those rights? This course helps everyone from laypersons to data science and business professionals understand and move forward in one of the most important issues of our time: In a world driven by data, who owns this valuable resource? Analyst Martin Kemka, a specialist in machine learning and applied AI, helps you understand your rights and how to protect them. He also helps those who work with data understand their responsibilities, including the global policies guiding AI research and applications. Umfang: 00:35:19.00
Inhalt: What does it mean to design responsible AI algorithms? Instructor Martin Kemka introduces important basics, like defining AI and knowing what it means to be responsible in developing them. Learn how algorithms are deployed and how you can track their use and abuse. Martin also explains the risks of being irresponsible with AI. Find out how an algorithm is created and how you can monitor it. Examine the decision side of the system. Hear about global policies and best practices. Learn how policies differ from one country to another, explore open-source software solutions, and more. Umfang: 00:38:49
Inhalt: SageMaker is Amazon's solution for developers who want to deploy predictive machine learning models into a production environment. Programming is done in Python and the results can easily be integrated into cloud-based applications. These lessons review the entire Amazon SageMaker workflow: analysis, build, and final deployment. Instructor Martin Kemka introduces the benefits of Amazon SageMaker and reviews its browser-based interface and toolset. In the second chapter, he shows how to import, investigate, visualize, and summarize your data. The next stage is to use a clean data sample to train a machine learning model to fulfill a basic task. Finally, Martin shows how the model is deployed. Almost every chapter concludes with a challenge that allows you to practice your new SageMaker skills. Umfang: 01:11:54.00
Inhalt: Massive computing power, research, and open-source code have made artificial intelligence (AI) accessible to everyone. But with great power comes great responsibility. As more businesses incorporate AI into their strategies, it's critical for executives and analysts alike to ensure AI isn''t being deployed for harmful purposes. This course is designed so that a general audience, ranging from business and institutional leaders to specialists working on data teams, can identify the proper application of AI and understand the ramifications of their decisions regarding its use. Instructor Martin Kemka provides a global perspective, reviewing the current policies and laws guiding image recognition, automation, and other AI-driven technologies, and explores what AI holds in store for our future. Umfang: 00:36:51.00
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