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IoT Fundamentals

Get started with Internet of Things (IoT) from sensors and actuators, to IoT networking fundamentals, and data analytics with machine learning

Rob Barton
Jerome Henry

The Internet of Things (IoT) is one of the most disruptive suite of technologies the world has ever seen. It is fundamentally changing business processes and improving efficiencies in ways we have never seen. However, IoT is a complex subject that leverages a host of integrated technologies, including wireless network architectures, data analytics, and machine learning.

What you'll learn-and how you can apply it

This training course will introduce you to the technical foundations of IoT, from the sensors and actuators, through secure IoT network access technologies, all the way to the core aspects of big data analytics and machine learning.

However, understanding the underlying technologies is only the beginning. This course will further discuss how these technologies are being used in various industries and will explore best-practice architectures that can be leveraged to harness the power of IoT.

Participants will understand:

  • Network technologies used in IoT
  • How data analytics provides business insights
  • The role of machine learning
  • How IoT is being used across multiple industries
  • The principles of IoT security
  • Participants will be able to…
  • Choose the right IoT technology for their network
  • Leverage IoT for business value
  • Secure their IoT network
  • Choose the right machine learning algorithm for their IoT data

This training course is for you because...

  • You want to understand the practical aspects of IoT and how what you need to know to get started
  • You are a network engineer, analyst, or architect and you want to learn about core IoT network architectures
  • You are interested in Big Data architectures and Machine Learning, and how it can be used in IoT
  • You want to learn about emerging IoT network technologies, including LoRaWAN, NB-IoT, and Fog computing
  • You want to learn how IoT can be used in key industries, including Smart Cities, Transportation systems, Manufacturing, and others.

Prerequisites

  • Basic understanding of network communications, wireless technologies (Wi-Fi, LTE), and data management systems

Recommended preparation:

Internet of Things (IOT) Fundamentals LiveLessons (video)

About your instructor

  • Rob Barton, CCIE #6660 (R&S and Security), CCDE 2013::6 is a Principal Systems Engineer working in Cisco's Digital Transformation and Innovation group. Rob is a registered Professional Engineer (P. Eng) and has worked in the IT industry for over 20 years, the last 17 of which have been at Cisco. Rob Graduated from the University of British Columbia with a degree in Engineering Physics. Rob is a Cisco Press published author, with titles including QoS, Wireless, and IoT. Over the past five years, Rob has worked on some of the largest IoT deployments in the world, and is an expert in several IoT-related industries, such as utilities. His areas of interest include wireless communications, IPv6, IoT, and industrial control systems. Rob is also a multi-year recipient of the Cisco Live Distinguished speaker award.

  • Jerome Henry is Principal Engineer in the Enterprise Infrastructure and Solutions Group at Cisco systems. Jerome has more than 15 years experience teaching technical Cisco courses in more than 15 different countries and 4 different languages, to audiences ranging from Bachelor degree students to networking professionals and Cisco internal system engineers. Focusing on his wireless experience, Jerome joined Cisco in 2012. Before that time, he was consulting and teaching Heterogeneous Networks and Wireless Integration with the European Airespace team, which was later acquired by Cisco to become their main wireless solution. He then spent several years with a Cisco Learning partner, developing technical courses, and working on training material for new technologies. He is certified wireless networking expert (CWNE #45), CCIE Wireless (#24750), CCNP Wireless, developed several Cisco courses focusing on wireless topics and authored several books and video courses on Wireless, IoT and networking. Jerome is also an IEEE member, where he was elevated to the grade of Senior Member in 2013, and also participates to Wi-Fi Alliance working groups. With more than 10000 hours in the classroom, Jerome was awarded the IT Training Award best Instructor silver medal. He is based in RTP, NC.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing

DAY 1

Introductions (15 min)

  • Name, role, goals for this class
  • What is IoT?
  • How IoT is transforming business (with examples)
  • Types of IoT – industrial, commercial, etc.

Lecture: An introduction to IoT Architectures (20 min)

  • Comparing IoT architectures
  • Industrial IoT architectures (ISA-99 / IEC 62443)

Lecture: Sensors and Actuators (20 min)

  • An overview of sensors and actuators in an IoT network
  • Typical network requirements of sensors and actuators
  • Examples

BREAK (10 min)

Lecture: Connecting IoT Devices to a Network (25 min)

  • The IoT wireless landscape (RFID, Wi-Fi)
  • LPWA Technologies (LoRaWAN, NB-IoT)
  • IoT and 802.15.4 Mesh Networks

Lecture: Connecting IoT Devices with IPv6 (25 min)

  • A quick IPv6 refresher
  • IPv6 in lossy networks (6LoWPAN)
  • Routing in IoT (RPL)

BREAK (10 min)

Lecture: Managing IoT Devices (25 min)

  • An overview of management requirements in IoT
  • Managing constrained devices (CoAP)
  • MQTT
  • SCADA

Lecture: Securing IoT Networks (30 min)

  • IoT threat vectors
  • Security architectures for IoT
  • Case Study – the anatomy of an attack on an IoT system

DAY 2

Lecture: Leveraging the power of IoT Data with analytics (30 min)

  • Data architectures for IoT
  • An introduction to Hadoop
  • Network vs. Data analytics

Lecture: Fog Computing – Analytics at the Edge (35 min)

  • Streaming vs. Batch Analytics
  • What is Fog Computing?
  • Fog Computing architectures

BREAK (10 min)

Lecture: Machine Learning (30 min)

  • How Machine Learning is used in IoT
  • Supervised Learning: Linear and Logistic Regression, neural networks
  • ML Applications to IoT (e.g. video analytics)

Lecture: IoT and Industry Part 1 (22 min)

  • Smart connected cities
  • Transportation systems

Lecture: IoT and Industry Part 2 (23 min)

  • Manufacturing
  • Retail