In this unit, students explore synthetic media by creating a smartphone app …
In this unit, students explore synthetic media by creating a smartphone app that can speak in different voices by changing the rate and pitch of the speech. Students work in groups to present arguments about the possible future impacts of various types of deepfake media, including ones in commerce and assistive technology as well as those used in crime.
Educators can use this lesson to introduce students to coding, provide a basic understanding of artificial intelligence and machine learning, and prompt students to predict the possible future use and abuse of synthetic media in society.
This course about financial technology, or FinTech, is for students wishing to …
This course about financial technology, or FinTech, is for students wishing to explore the ways in which new technologies are disrupting the financial services industry—driving material change in business models, products, applications and customer user interface. Amongst the significant technological trends affecting financial services into the 2020’s, the class will explore AI, deep learning, blockchain technology and open APIs. Students will gain an understanding of the key technologies, market structure, participants, regulation and the dynamics of change being brought about by FinTech.
Advances in cognitive science have resolved, clarified, and sometimes complicated some of …
Advances in cognitive science have resolved, clarified, and sometimes complicated some of the great questions of Western philosophy: what is the structure of the world and how do we come to know it; does everyone represent the world the same way; what is the best way for us to act in the world. Specific topics include color, objects, number, categories, similarity, inductive inference, space, time, causality, reasoning, decision-making, morality and consciousness. Readings and discussion include a brief philosophical history of each topic and focus on advances in cognitive and developmental psychology, computation, neuroscience, and related fields. At least one subject in cognitive science, psychology, philosophy, linguistics, or artificial intelligence is required. An additional project is required for graduate credit.
This course is an introduction to computational biology emphasizing the fundamentals of …
This course is an introduction to computational biology emphasizing the fundamentals of nucleic acid and protein sequence and structural analysis; it also includes an introduction to the analysis of complex biological systems. Topics covered in the course include principles and methods used for sequence alignment, motif finding, structural modeling, structure prediction and network modeling, as well as currently emerging research areas.
The emergence of transformer architectures in 2017 triggered a breakthrough in machine …
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.
How are math, art, music, and language intertwined? How does intelligent behavior …
How are math, art, music, and language intertwined? How does intelligent behavior arise from its component parts? Can computers think? Can brains compute? Douglas Hofstadter probes very cleverly at these questions and more in his Pulitzer Prize winning book, “Gödel, Escher, Bach”. In this seminar, we will read and discuss the book in depth, taking the time to solve its puzzles, appreciate the Bach pieces that inspired its dialogues, and discover its hidden tricks along the way.
The projects in this guide use a student-driven approach to learning. Instead …
The projects in this guide use a student-driven approach to learning. Instead of simply learning about AI through videos or lectures, the students completing these projects are active participants in their AI exploration. In the process, students work directly with innovative AI technologies, participate in “unplugged” activities that further their understanding of how AI technologies work, and create various authentic products—from machine learning models to video games—to demonstrate their learning.
Project 1: Programming with Machine Learning Project 2: AI-Powered Players in Video Games Project 3: Using AI for Robotic Motion Planning Project 4: Machine Learning as a Service
Visit the ISTE website with all the free practical guides for engaging students in AI creation: https://www.iste.org/areas-of-focus/AI-in-education
This guide provides student-driven projects that can directly teach subject area standards …
This guide provides student-driven projects that can directly teach subject area standards in tandem with foundational understandings of what AI is, how it works, and how it impacts society. Several key approaches were taken into consideration in the design of these projects. Understanding these approaches will support both your understanding and implementation of the projects in this guide, as well as your own work to design further activities that integrate AI education into your curriculum.
Project 1: AI Chatbots Project 2: Developing a Critical Eye Project 3: Using AI to Solve Environmental Problems Project 4: Laws for AI
Visit the ISTE website with all the free practical guides for engaging students in AI creation: https://www.iste.org/areas-of-focus/AI-in-education
In this guide, students’ exploration of AI is framed within the context …
In this guide, students’ exploration of AI is framed within the context of ethical considerations and aligned with standards and concepts, and depths of understanding that would be appropriate across various subject areas and grade levels in K–12. Depending on the level of your students and the amount of time you have available, you might complete an entire project, pick and choose from the listed activities, or you might take students’ learning further by taking advantage of the additional extensions and resources provided for you. For students with no previous experience with AI education, exposure to the guided learning activities alone will create an understanding of their world that they likely did not previously have. And for those with some background in computer science or AI, the complete projects and resources will still challenge their thinking and expose them to new AI technologies and applications across various fields of study.
Project 1: Fair's Fair Project 2: Who is in Control? Project 3: The Trade-offs of AI Technology Project 4: AI and the 21st Century Worker
Visit the ISTE website with all the free practical guides for engaging students in AI creation: https://www.iste.org/areas-of-focus/AI-in-education.
As the digital revolution brings with it radical changes in how and …
As the digital revolution brings with it radical changes in how and what we learn, people must continue to learn all the time. New technologies make possible new approaches to learning, new contexts for learning, new tools to support learning, and new ideas of what can be learned. This course will explore these new opportunities for learning with a special focus on what can be learned through immersive, hands-on activities. Students will participate in (and reflect on) a variety of learning situations, and will use Media Lab technologies to develop new workshops, iteratively run and refine the workshops, and analyze how and what the workshop participants learn.
How to Train Your Robot was originally developed as an extension of …
How to Train Your Robot was originally developed as an extension of the AI + Ethics for Middle School curriculum. In its current form, How to Train Your Robot provides a full, one-week of activities that allow middle school students to explore artificial intelligence and ethics through hands-on activities.
In this course, students participate in a range of hot-topic discussions and hands-on, creative activities to learn about how artificial intelligence is impacting society today. Students will design robot companions to solve real-world problems and use machine learning to make them intelligent. At the end of the course, you will have designed your very own robot companion to share with the world.
This course analyzes seminal work directed at the development of a computational …
This course analyzes seminal work directed at the development of a computational understanding of human intelligence, such as work on learning, language, vision, event representation, commonsense reasoning, self reflection, story understanding, and analogy. It reviews visionary ideas of Turing, Minsky, and other influential thinkers and examines the implications of work on brain scanning, developmental psychology, and cognitive psychology. There is an emphasis on discussion and analysis of original papers; students taking the graduate version complete additional exercises and a substantial term project.
The strategic importance of information technology is now widely accepted. It has …
The strategic importance of information technology is now widely accepted. It has also become increasingly clear that the identification of strategic applications alone does not result in success for an organization. A careful coordination of strategic applications, information technologies, and organizational structures must be made to attain success. This course addresses strategic, technological, and organizational connectivity issues to support effective and meaningful integration of information and systems. This course is especially relevant to those who wish to effectively exploit information technology and create new business processes and opportunities.
This is an introductory course on computational thinking. We use the Julia …
This is an introductory course on computational thinking. We use the Julia programming language to approach real-world problems in varied areas, applying data analysis and computational and mathematical modeling. In this class you will learn computer science, software, algorithms, applications, and mathematics as an integrated whole. Topics include image analysis, particle dynamics and ray tracing, epidemic propagation, and climate modeling.
This half-semester course introduces computational thinking through applications of data science, artificial …
This half-semester course introduces computational thinking through applications of data science, artificial intelligence, and mathematical models using the Julia programming language. This Spring 2020 version is a fast-tracked curriculum adaptation to focus on applications to COVID-19 responses. See the MIT News article Computational Thinking Class Enables Students to Engage in Covid-19 Response
This is MIT’s introductory course on deep learning methods with applications to …
This is MIT’s introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), and we’ll try to explain everything else along the way! Experience in Python is helpful but not necessary.
This course introduces principles, algorithms, and applications of machine learning from the …
This course introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction. It includes formulation of learning problems and concepts of representation, over-fitting, and generalization. These concepts are exercised in supervised learning and reinforcement learning, with applications to images and to temporal sequences. 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 resource includes a set of activities, teacher guides, assessments, materials, and …
This resource includes a set of activities, teacher guides, assessments, materials, and more to assist educators in teaching about the ethics of artificial intelligence. These activities were developed at the MIT Media Lab to meet a growing need for children to understand artificial intelligence, its impact on society, and how they might shape the future of AI.
This course introduces students to machine learning in healthcare, including the nature …
This course introduces students to machine learning in healthcare, including the nature of clinical data and the use of machine learning for risk stratification, disease progression modeling, precision medicine, diagnosis, subtype discovery, and improving clinical workflows.
This course covers fundamental and advanced techniques in this field at the …
This course covers fundamental and advanced techniques in this field at the intersection of computer vision, computer graphics, and geometric deep learning. It will lay the foundations of how cameras see the world, how we can represent 3D scenes for artificial intelligence, how we can learn to reconstruct these representations from only a single image, how we can guarantee certain kinds of generalizations, and how we can train these models in a self-supervised way.
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