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MOOC
AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone--especially your non-technical colleagues--to take. In this course, you will learn: - The meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science - What AI realistically can--and cannot--do - How to spot opportunities to apply AI to problems in your own organization - What it feels like to build machine learning and data science projects - How to work with an AI team and build an AI strategy in your company - How to navigate ethical and societal discussions surrounding AI
- Subjects:
- Computing
- Keywords:
- Artificial intelligence
- Resource Type:
- MOOC
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Video
In this lecture, we consider strategies for adversarial games such as chess. We discuss the minimax algorithm, and how alpha-beta pruning improves its efficiency. We then examine progressive deepening, which ensures that some answer is always available.
- Course related:
- COMP4431 Artificial Intelligence
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Artificial intelligence
- Resource Type:
- Video
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Video
This video is take an adapted version of this course as part of the Stanford Artificial Intelligence Professional Program.
- Course related:
- AP619 Microfabrication Laboratory
- Subjects:
- Computing
- Keywords:
- Machine learning Computer algorithms
- Resource Type:
- Video
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e-book
This textbook is based on the MOOC Responsible Innovation offered by the TU Delft. It provides a framework to reflect on the ethics and risks of new technologies. How can we make sure that innovations do justice to social and ethical values? How can we minimize (unknown)risks?The book explains: The concept and importance of responsible innovation for society Key ethical concepts and considerations to analyse the risks of new technologies Different types of innovation (e.g. radical, niche, incremental, frugal) Roadmap for Responsible Innovation by Industry The concept of Value Sensitive Design (VSD) It includes a link to all the web lectures as well as case studies ranging from care robots and nuclear energy to Artificial Intelligence and self-driving vehicles.
- Subjects:
- Philosophy
- Keywords:
- Risk management Technological innovations -- Moral ethical aspects Textbooks
- Resource Type:
- e-book
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e-book
As schools, as well as the workplace, become more automated, and remote or distance learning/working becomes the “new normal,” understanding and leveraging artificial intelligence will become a critical skill.
- Keywords:
- Report writing Grading marking (Students) -- Computer programs Textbooks
- Resource Type:
- e-book
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e-book
Este libro es una introducción al area de la Inteligencia Artificial y presenta algunas de las aplicaciones que puede tener en la vida real en diversos campos de aplicación, El libro esta compuesto de ocho capítulos los cuales abarcan los antededentes, algunos conceptos importantes para la resolución de problemas como es la representación de conocimiento, el planteamiento de los problemas. Asimismo se menciona la teoría de agentes por un lado y por otro lo que es el aprendizaje computacional. Otra area que se aborta es la computación evolutivo y los algoritmos bioinspirados para la resolución de problemas, dandole enfasis a los problemas de optimizacion. Por ultimo se menciona una nueva tendencia en el area de las ciencias computacionales como es el uso de las GPUs para trabajar de una manera mas rapida al realizar el procesamiento en paralelo.
- Subjects:
- Computing
- Keywords:
- Artificial intelligence Textbooks
- Resource Type:
- e-book
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e-book
A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.
- Subjects:
- Computing
- Keywords:
- Data mining Computer science Artificial intelligence Textbooks
- Resource Type:
- e-book
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Courseware
Stanford Engineering Everywhere (SEE) expands the Stanford experience to students and educators online and at no charge. A computer and an Internet connection are all you need. The SEE course portfolio includes one of Stanford's most popular sequences: the three-course Introduction to Computer Science, taken by the majority of Stanford’s undergraduates, as well as more advanced courses in artificial intelligence and electrical engineering.
- Course related:
- EE1D01 Electrical Science for Everyone
- Subjects:
- Electronic and Information Engineering, Biomedical Engineering, Mechanical Engineering, and Computing
- Keywords:
- Engineering Computer science
- Resource Type:
- Courseware
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MOOC
The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.
- Course related:
- COMP4431 Artificial Intelligence
- Subjects:
- Computing
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
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MOOC
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.
- Course related:
- AMA564 Deep Learning
- Subjects:
- Computing
- Keywords:
- Machine learning Neural networks (Computer science) Artificial intelligence
- Resource Type:
- MOOC