Overview What You Will Learn Curriculum Instructor

Course Overview

Machine Learning systems are now widely used in distributed systems, taking advantage of the public cloud infrastructure. While more accurate ML models continue increasing in size, TinyML applications start to appear on the other end of the spectrum. From Alexa to smart bulbs, autonomous cars, security cameras and all kinds of smart sensors can now run small Neural Networks, opening a window of opportunity for new businesses never thought of before. 

In this course, we introduce the main concepts of Deep Learning and different types of Embedded systems which are currently used in the industry. Then we will explore the state-of-the-art techniques and frameworks to reduce the size of Neural Networks so that they can run in constrained devices. Finally, we show several hands-on examples which you can follow along and reproduce using your physical Development Kit if available. We will use an Arduino Nano 33 BLE Sense, but you can use another similar device (at your own risk!) or just follow the videos along. 

At the end of this course, you will be able to describe in detail the most common methods used to compress Deep Neural Networks and apply some of them in real-life applications. This may be your first step in landing a new cool job in AIoT, the intersection of AI and IoT, or creating a new business opportunity with an innovative product!

The necessary resources for this course are in the "Resources" section of Video 1.1. You can also access them through this direct link - https://github.com/ec-council-learning/Hands-on-TinyML

What You Will Learn

  • Understand the most popular Neural Networks and why they are becoming mainstream now
  • Learn the reasons why AIoT (AI + IoT) is the “next big thing”
  • Learn to Compress a Neural Network to make it run in a constrained device
  • Familiarize with Creating your own Neural Network from scratch
  • Familiarize with current and upcoming applications using Deep Neural Networks in Embedded system

Program Curriculum

  • Knowledge and Technical Pre-requisites
  • $7 Million Cybersecurity Scholarship by EC-Council

  • From Classical Software to Machine Learning Systems
  • Convolutional Neural Networks
  • Exercise: Train Your Own CNN
  • Machine Learning in Production Systems (MLOps)
  • Chatper 2 Quiz

  • Introduction to Embedded Systems
  • ARM Ecosystem
  • Wireless Technology
  • Exercise: Flashing to Arduino Nano 33 BLE Sense
  • PoC to Production
  • Chapter 3 Quiz

  • From Big Cluster to Tiny Devices
  • Hardware Accelerators
  • Software Support
  • Startup Ecosystem
  • Chatper 4 Quiz

  • TinyML Use-cases
  • Chatper 5 Quiz

  • Quantization and Pruning
  • Knowledge Distillation
  • TensorFlow Lite for Microcontrollers
  • Exercise: Compress Your Neural Network
  • Alternatives to TensorFlow Lite
  • Chatper 6 Quiz

  • Beyond TinyML
  • Chapter 7 Quiz
Load more modules

Instructor

Carlos HernandezVaquero

Carlos is a Program Manager in the areas of AI and IoT at Bosch in Germany. He previously took the role of Project Security Manager, Software Product Owner, and Software Engineer. During the last few years, he has led the development until the market release of 4 Bosch IoT products, several data-centric development activities, and over 20 mobile apps with teams distributed around Europe and Asia. In parallel to his job, he is a researcher in Machine Learning systems as a Ph.D. student. He has founded and currently organizes the TinyML community in Germany with over 350 members. He also likes to give back as an AWS Community Builder in the ML category, Microsoft Learn Student Ambassador, GitHub Campus Expert, and Super-Mentor in several of the DeepLearning.ai Coursera specializations. He has over 12 technical certifications from AWS, Microsoft Azure, Oracle Cloud Infrastructure, and CompTIA, most of them in the Cybersecurity and ML domains. Lately, he is participating as a Program Mentor in the IBM Hyper Protect Accelerator program, advising promising Startups in the Cybersecurity space. Carlos likes to keep learning and researching to be always at the front of innovation with an open mind and positive spirit. He will be happy to connect over LinkedIn and discuss with you in a pro-bono mentoring session in The Mentoring Club.

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