Foundation of Cloud IOT Edge ML

Course Duration: 8 Weeks

@VTU COE

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(0) 75 Students
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What you will learn

  • Computer Science and Engineering

The disrupted conventional computing models for internet of things(IoT), cloud computing, machine learning and embedded technologies have emerging computing paradigms called as Edge Computing . Computing has taken many shapes from edge to cloud. This course has been designed with an objective to provide a comprehensive understanding of relevant technologies (IoT, ML and Cloud) for various emerging computing paradigms of Edge Computing. Emerging applications of Internet of Things (IoT) such as augmented reality, self-driving cars, and many more are delay sensitive and computation intensive involve computing with large amount of data generated from massively distributed end users require real-time processing. Although the success of cloud computing for supporting high performance computing has been witnessed in recent years, its inefficiency in quality of service (QoS) provisioning for delay sensitive applications as well as high energy consumption has been the bottleneck for the development of delay-sensitive IoT applications. Edge computing has recently emerged as an extension to cloud computing for QoS provisioning for delay-sensitive applications. It supports cloud-like computing in the network edge by deploying computing and network resources along the path between data source and cloud datacenters. This course provides an in-depth understanding of terminologies and the core concepts behind Cloud-IoT-Edge problems, applications, systems and the techniques, that underlie today's cutting-edge technologies. It provides an introduction to some of the start-of-the-art IoT and wireless networks, edge and virtualization technologies, recent trends in computer hardware for artificial intelligence, spatial localization and detection, tensor processing unit for fast and affordable artificial intelligence (AI). And while discussing the concepts and techniques, we will also look at various applications of Cloud-IoT-Edge using Machine Learning, Deep Learning, and many others. The course is suitable for all UG/PG students and practicing engineers/ scientists from the diverse fields and interested in learning about the novel cutting edge techniques and applications of Cloud-IoT-Edge.

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Lecture 1 Introduction to Edge Computing 23 12 2022 V1
Preview 37:46
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Lecture 2 Introduction to Cloud 23 12 2022 V2
Preview 52:39

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Lecture 3 Introduction to IoT Platform 24 12 2022 V1
Preview 46:37
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Lecture 4 Time and Clock Synchronization in IoT 24 12 2022 V2
Preview 52:32

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Lecture 5
Preview 54:11
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Lecture 6
Preview 56:19

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Lecture 7 Introduction to Docker Containers and Kubernetes 26 12 2022 V2
Preview 33:59
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Lecture 8 ML based Predictive Maintenance at IoT Edge 28 12 2022 V1
Preview 59:12

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Lecture 9: Deep Reinforcement Learning for Cloud Edge
Preview 69:38
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Lecture 10 Deep Reinforcement Learning for Cloud Edge Example
Preview 21:56
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Lecture 11 Public Cloud Services Case Study of AWS Services
Preview 53:05

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Lecture 12: Mathematical formulations for task offloading in Edge Cloud
Preview 46:37
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Lecture 13: Task Offloading Based on LSTM Prediction and Deep Reinforcement Learning
Preview 43:24
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Lecture 14: Vertical and Horizontal Offloading for Cloud Edge
Preview 19:38
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Lecture 15: Global State and Snapshot Recording Algorithms
Preview 32:05

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Lecture 16: Hot Data Analytics for Real Time Streaming in IoT Platform
Preview 52:46
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Lecture 17: Introduction to MQTT and Kafka in IoT Platform
Preview 45:09
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Lecture 18: Introduction to Edge Data Center for IoT Platform
Preview 61:15
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Lecture 19: Design of Key Value Stores for IoT Edge Storage
Preview 64:10

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Lecture 20: Introduction to Edge ML with AWS IoT platform
Preview 56:37
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Lecture 21: Introduction to Federated Learning at IoT Edge
Preview 55:50
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Lecture 22: ML for Autonomous Driving Car
Preview 42:39
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Meet Your Instructor

Instructor
3.4 Rating
24108 Students
904 Courses
About Instructor

VTU is one of the largest Technological Universities in India with 24 years of Tradition of excellence in Engineering & Technical Education, Research and Innovations. It came into existence in the year 1998 to cater the needs of Indian industries for trained technical manpower with practical experience and sound theoretical knowledge.

video

Free

  • Course Duration
    17 h 38 m 4 s
  • Course Level
    Intermediate
  • Student Enrolled
    75
  • Language
    English
This Course Includes
  • 17 h 38 m 4 s Video Lectures
  • 2 Quizzes
  • 0 Assignments
  • 0 Downloadable Resources
  • Full Lifetime Access
  • Certificate of Completion