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Technology Application and Innovation
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MOOC
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MOOC
Explore the frontiers of technology, predict the future, and thrive in an ever-changing world. Our immersive course combines cutting-edge insights, expert guidance, and creative vision to help you become a disruptor, not a bystander. From emerging technology to AI to storytelling and speculative design, gain the knowledge and skills to shape tomorrow's opportunities. Embrace innovation, foresee challenges, and chart your path in the era of disruption. Join us now and unlock your potential to lead and innovate in a dynamic digital landscape.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Technology Information technology Artificial intelligence
- Resource Type:
- MOOC
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MOOC
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.
- Course related:
- AAE5103 Artificial Intelligence in Aviation Industry
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
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MOOC
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Python (Computer program language)
- Resource Type:
- MOOC
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MOOC
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
- Course related:
- COMP4434 Big Data Analytics and EIE6207 Theoretical Fundamental and Engineering Approaches for Intelligent Signal and. Information Processing
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
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MOOC
In the past few decades, China's cities have experienced a period of rapid development. Great changes have taken place in both urban space and urban life. With the booming of information and communications technology (ICT), ‘Big data’ such as mobile phone signaling, public transportation smart card records and ‘open data’ from commercial websites and government websites jointly promote the formation of the ‘new data environment’, thus providing a novel perspective for a better understanding of what changes have happened or are happening in China’s cities. This course combines both the new data generated for urban analysis and its research applications. The content ranges from big data acquisition, analysis, visualization and applications in the context of China’s urbanization and its city planning, to urban modeling methods and typical models, as well as the emerging trend and potential revolution of big data in urban planning. We have categorized the overall content of this online course into five sections, namely, overview, data, data processing, application, and perspective. The section of overview introduces cities in transition and describe the changing of urban space and urban life in China. The second section lists some commonly used open data and big data in the ‘new data environment’. Then, methods for data acquisition, cleaning and analysis are illustrated in data processing section. To better explain the data analysis method, the fourth part introduces several Chinese research cases to illustrate the application of these methods in urban research. Last but not least, the last section is the most future-oriented one, which is composed of some methodologies and proposals such as Data Augmented Design (DAD) and Big Model. This course, which shares experiences on big data analysis and its research application, will suit those concerning contemporary urbanizing China and its urban planning in the context of information and communication technologies.
- Subjects:
- Building Services Engineering and Building and Real Estate
- Keywords:
- China Cities towns -- Data processing City planning Big data
- Resource Type:
- MOOC
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MOOC
Learn about information and communication technologies [ICTs] and innovations in the hotel and tourism industries.
- Subjects:
- Hotel, Travel and Tourism
- Keywords:
- Hospitality industry Tourism Technological innovations
- Resource Type:
- MOOC