TENTATIVE PROGRAMME |
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Day 1 – 16 November 2020 |
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9:00 am – 9:40 am |
Opening Ceremony (Zoom) Welcome Address by Organizers Dr Liu Chang, Director of Division of International Cooperation, IKCEST Madam Tengku Sharizad Tengku Dahlan, Director, ISTIC |
Zoom
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9:40 am – 10:00 am |
An Introduction to IKCEST by Ms Zhang Ye (Jenny) and ISTIC by Mr Mohd Azim Noor (Programme Manager, ISTIC) |
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10:00 am – 12:00 pm |
Introduction to Big Data and Deep learning Dr Lyu Na |
IKCEST Platform
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12:00 pm – 1:00 pm |
Break |
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1:00 pm – 3:00 pm |
Introduction to Big Data Platforms and Applications of Big Data Technology Dr Tian Feng |
IKCEST Platform
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Day 2 – 17 November 2020 |
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10:00am – 11:30 am |
From Quarantine to Cloud Computing Dr Shi Bin |
IKCEST Platform
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10:00am – 11:30 am |
Frontier of Cloud - Green Data Center Dr Shi Bin |
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Day 3 – 18 November 2020 |
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10:00 am – 11:30 am |
Introduction to Machine Learning Dr Luo Minnan |
IKCEST Platform |
11:30 am – 1:00 pm |
Network Representation Learning and Its Applications Dr Luo Minnan |
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1:00 pm - 1:30 pm |
Presentation of lessons learnt from participants Online Discussion (Zoom) |
Zoom
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1:30pm -1:50pm |
Grad Ceremony (Online Assessment, Online Examination) |
IKCEST Platform
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Introduction to Big Data and Deep learning
Abstract: This course introduces the methods and frontiers in big data processing and analysis,machine learning, deep learning and data mining. The representative big data processing platform
Hadoop and the classic big data analysis mechanism Map-reduce will be introduced. The foundations of machine learning and artificial intelligence will be discussed, including linear regression, logistic regression, neural networks, other supervised learning and unsupervised learning methods. The concept and motivation of deep learning will be discussed. The breakthrough methods in deep learning, including auto Encoder, Restricted Boltzmann Machine, and Convolutional Neural Network will be introduced. Take the benchmark competitions as examples, the applications of deep learning and big data analysis will be introduced.
Speaker: Lyu Na, Ph.D., Professor
School of Automation, Xi'an Jiaotong University
Dean of Shaanxi Province Advanced Robot Control Engineering Laboratory
Introduction to Big Data Platforms and Applications of Big Data Technology
Abstract: This talk gives a brief introduction to big data technology and platforms. To be specific,history, original, and supporting technology of the era of big data are reviewed. Next, shows fourparadigms of experiment, theory, calculation and data in scientific research. Then, discusses the related topics on AI, Data Science, and data mining, as well as supervised and unsupervised method.Finally, briefly describes a few big data platforms, for an example, MapReduce. This talk also gives several applications of Big Data Technology in the fields, such as disease control, education. To begin with, introduce COVID-19 and control plan of China. Next, introduce a real-time monitoring big data platform of higher education teaching quality.
Speaker: Tian Feng, Ph.D., Professor
School of Automation, Xi'an Jiaotong University
From Quarantine to Cloud Computing
Abstract: Cloud computing is a kind of distributed computing. It refers to the decomposition of huge data calculation processing programs into countless small programs through the network "cloud".Then, through the system composed of multiple servers, processing and analyzing these small programs to obtain the results and return to the user. After ten years of development, cloud computing has become a very mature and efficient technology, and has achieved very good results in terms of computing power and energy consumption. In the COVID-19 epidemic, a large number of students began to use online classrooms for learning, and the demand for computing power surged. Cloud computing solves this problem elegantly through its elasticity and dynamic characteristics. This lecture will introduce the basic principles, features and advantages of cloud computing. Then introduce the research of the latest frontier areas, pointing out the current open issues and possible directions of cloud computing. Through this lecture, it will help to better understand cloud computing and learn about the latest research hotspots.
Speaker: Shi Bin, Ph.D., Assistant Professor
School of Computer Science and Technology, Xi'an Jiaotong University
Frontier of Cloud - Green Data Center
Abstract: In recent years, the concept of green world, environmental protection and sustainable development has gradually become popular and penetrated into all walks of life. This is no exception for computer systems, and the concept of the green data center is proposed under this background.The meaning of the green data center is to improve the energy efficiency of the data center, minimize the overall power consumption of the data center, maximize the proportion of the IT system in the overall data center power consumption, minimize the power consumption for non-computing equipment (power conversion, cooling, etc.). Green data center has become an important concept and goal of cloud computing technology development. This lecture introduces the relevant technologies of green data center, including virtualization technology, data center scheduling technology, and virtual machine migration technology. This lecture will help you better understand cloud computing and data center management, and current research hotspots.
Speaker: Shi Bin, Ph.D., Assistant Professor
School of Computer Science and Technology, Xi'an Jiaotong University
Introduction to Machine Learning
Abstract: Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. In this course, we will talk something about machine learning, including the evolution of machine learning, why is machine learning important, and some popular machine learning methods and its applications.
Speaker: Luo Minnan, Ph.D., Associate Professor
School of Computer Science and Technology, Xi'an Jiaotong University
Network Representation Learning and Its Applications
Abstract: A variety of data in many different fields can be described by networks, such as the WorldWide Web, social networks of acquaintances or other types of interactions, networks of publications linked by citations, transportation networks, metabolic network, and communication networks. In this talk, we will recall some basic concepts and preliminaries of network in mathematics, and then introduce the representation learning of network in the framework of machine learning, togetherwith some applications.
Speaker: Luo Minnan, Ph.D., Associate Professor
School of Computer Science and Technology, Xi'an Jiaotong University
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