This video aims to delve into the human problems brought out by issues in artificial intelligence, specifically with respect to bias. It is suitable for classroom use or as a standalone video for those who wish to understand the issue more deeply than is conventionally covered. For classroom use, we recommend watching the chapterized version of the video and working through the teaching materials provided for each chapter.

This course introduces the tools of philosophical ethics through application to contemporary issues concerning technology. It takes up current debates on topics such as privacy and surveillance, algorithmic bias, the promise and peril of artificial intelligence, automation and the future of work, and threats to democracy in the digital age from the perspective of users, practitioners, and regulatory/governing bodies.

Midterm Exam Review for the course "CSC 59970 – Intro to Data Science" delivered at the City College of New York in Spring 2019 by Grant Long as part of the Tech-in-Residence Corps program.

Midterm Exam and Answer Key for the course "CSC 59970 – Intro to Data Science" delivered at the City College of New York in Spring 2019 by Grant Long as part of the Tech-in-Residence Corps program.

Midterm Exam Review for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Practice Final Exam for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

This course provides a comprehensive review of interoperability, health data standards, and other advanced topics including Substitutable Medical Applications, Reusable Technologies (SMART) and Fast Healthcare Interoperability Resources® (FHIR), also known as SMART-on-FHIR applications and Accelerator projects. This course will use Interoperability Land™ to provide learners with a hands-on experience using FHIR resources. Upon successful completion of this course, learners will be able to: explain interoperability and use cases; locate information within JSON and XML files; Create queries in IOL; understand SMART application authorization. Interoperability Land can be purchased on AWS Marketplace at the followinglink: https://aws.amazon.com/marketplace/pp/prodview-f34r2uj3naohe For information regarding education pricing please email contactus@interoperabilityinstitute.org.

In this dynamic data science game, students try to track down a speck of extremely dangerous radioactive material (the "source"), which has been lost somewhere in the middle of their lab. A special device measures the strength of the radiation and, if it’s positioned correctly over the speck, can be used to collect it for safe disposal. But it's a tiny speck, so they have to give quite precise coordinates. They take measurements to figure out the speck’s location, but must beware: as they take measurements, they're also accumulating radiation exposure. If they get too much, they’ll lose the game and will have to start over. Can they find the source before it’s too late? Using mathematical models, students generate useful strategies for winning the game with data.

The emergence of transformer architectures in 2017 triggered a breakthrough in machine learning that today lets anyone create computer-generated essays, stories, pictures, music, videos, and programs from high-level prompts in natural language, all without the need to code. That has stimulated fervent discussion among educators about the implications of generative AI systems for curricula and teaching methods across a broad range of subjects. It has also raised questions of how to understand both these systems and the at times overstated claims made for them. This class will introduce the foundations of generative AI technology, and participants will explore new opportunities it enables for K–12 education. It will also describe and explore how an analytical frame of mind can help make clear the core issues underlying both the successes and failures of these systems. Much of the work will be project-based, involving implementing innovative teaching and learning tools and testing these with K–12 students and teachers.

This course will explore innovations in information systems for health care delivery in developing countries, and focus not only on the importance of technology, but also on broader issues necessary for its success, such as quality improvement, project management, and leadership skills. 
This course is targeted toward individuals interested in designing or implementing a health information and communication technology (ICT) solution in the developing world. Implementing a health information technology project requires multidisciplinary teams. Thus, with this course, we hope to bring together individuals from a variety of disciplines—computer science, medicine, engineering, public health, policy, and business.
What you’ll learn:

Global health burden
Design thinking
Health informatics
Software development process
Evaluation and monitoring

This course is part of the Open Learning Library, which is free to use. You have the option to sign up and enroll in the course if you want to track your progress, or you can view and use all the materials without enrolling.

This class introduces the student to the use of small telescopes, either for formal research or as a hobby.
This course covers background for and techniques of visual observation, electronic imaging, and spectroscopy of the Moon, planets, satellites, stars, and brighter deep-space objects. Weekly outdoor observing sessions using 8-inch diameter telescopes when weather permits. Indoor sessions introduce needed skills. Introduction to contemporary observational astronomy including astronomical computing, image and data processing, and how astronomers work. Student must maintain a careful and complete written log which is graded. (Limited enrollment with priority to freshmen. Consumes an entire evening each week; 100% attendance at observing sessions required to pass.)

Lecture for the course "CSC 59970 – Intro to Data Science" delivered at the City College of New York in Spring 2019 by Grant Long as part of the Tech-in-Residence Corps program.

Homework for the course "CSC 59970 – Intro to Data Science" delivered at the City College of New York in Spring 2019 by Grant Long as part of the Tech-in-Residence Corps program.

Homework for the course "CSC 59970 – Intro to Data Science" delivered at the City College of New York in Spring 2019 by Grant Long as part of the Tech-in-Residence Corps program.

Homework for the course "CSC 59970 – Intro to Data Science" delivered at the City College of New York in Spring 2019 by Grant Long as part of the Tech-in-Residence Corps program.

Homework for the course "CSC 59970 – Intro to Data Science" delivered at the City College of New York in Spring 2019 by Grant Long as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Homework for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.

Lecture for the course "CS 217 – Probability and Statistics for Computer Science" delivered at the City College of New York in Spring 2019 by Evan Agovino as part of the Tech-in-Residence Corps program.