IPN-Dharma IA Lab

    Bienvenidos
    IPN-Dharma IA Lab

    Es una iniciativa de Laboratorio de Inteligencia Artificial del CIC del IPN con la colaboración de DHARMA para motivar a investigadores, profesores y estudiantes a aprovechar los cursos, recursos y herramientas de las principales plataformas tecnológicas de la industria en las áreas de Aprendizaje Automático, Ciencia de Datos, Computación en la Nube, Inteligencia Artificial e Internet de las Cosas con el propósito de generar una experiencia práctica a través de un modelo de aprendizaje entre pares y por objetivos.

    Nivel 1: Alfabetización y Fundamentos

    IoT for Beginners

    IoT for Beginners is a curriculum of 24-lesson all about IoT basics. Each lesson includes pre- and post-lesson quizzes, written instructions to complete the lesson, a solution, an assignment and more. The project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'.

    The projects cover the journey of food from farm to table. This includes farming, logistics, manufacturing, retail and consumer - all popular industry areas for IoT devices.

    Each lesson includes:

    • Sketchnote
    • Optional supplemental video
    • Pre-lesson warmup quiz
    • Written lesson
    • For project-based lessons, step-by-step guides on how to build the project
    • Knowledge checks
    • A challenge
    • Supplemental reading
    • Assignment
    • Post-lesson quiz

    Cursos en este programa

    1) IoT for Beginners

    The lessons are grouped so that you can deep-dive into use cases of IoT. We start with an introduction to IoT, covering devices, sensors, actuators and cloud connectivity, where you will build an internet connected version of the "Hello world" or IoT, an LED. We then move on to farming, learning about digital agriculture and feedback loops to control automated watering systems. Your food then leaves the farm on trucks, and you learn how to track vehicles using GPS, visualize their journeys and get alerts when a truck approaches a processing plant. Once in the plant, we move to AIoT, learning how to distinguish between ripe and unripe fruit using AI models running from IoT devices and on the edge. Next we move to the supermarket, using IoT to manage stock levels. Finally we take the food home to cook, and learn about consumer smart devices, building a voice controlled smart timer that can even speak multiple languages.

    Esfuerzo  Esfuerzo estimado 12 semanas

    Idioma  Idioma inglés

    Link  GitHub

    Getting started
    01
    Introduction to IoT
    Learn the basic principles of IoT and the basic building blocks of IoT solutions such as sensors and cloud services whilst you are setting up your first IoT device.
    02
    A deeper dive into IoT
    Learn more about the components of an IoT system, as well as microcontrollers and single-board computers.
    03
    Interact with the physical world with sensors and actuators
    Learn about sensors to gather data from the physical world, and actuators to send feedback, whilst you build a nightlight.
    04
    Connect your device to the Internet
    Learn about how to connect an IoT device to the Internet to send and receive messages by connecting your nightlight to an MQTT broker.
    Farm
    05
    Predict plant growth
    Learn how to predict plant growth using temperature data captured by an IoT device.
    06
    Detect soil moisture
    Learn how to detect soil moisture and calibrate a soil moisture sensor.
    07
    Automated plant watering
    Learn how to automate and time watering using a relay and MQTT.
    08
    Migrate your plant to the cloud
    Learn about the cloud and cloud-hosted IoT services and how to connect your plant to one of these instead of a public MQTT broker.
    09
    Migrate your application logic to the cloud
    Learn about how you can write application logic in the cloud that responds to IoT messages.
    10
    Keep your plant secure
    Learn about security with IoT and how to keep your plant secure with keys and certificates.
    Transport
    11
    Location tracking
    Learn about GPS location tracking for IoT devices.
    12
    Store location data
    Learn how to store IoT data to be visualized or analysed later.
    13
    Visualize location data
    Learn about visualizing location data on a map, and how maps represent the real 3d world in 2 dimensions.
    14
    Geofences
    Learn about geofences, and how they can be used to alert when vehicles in the supply chain are close to their destination.
    Manufacturing
    15
    Train a fruit quality detector
    Learn about training an image classifier in the cloud to detect fruit quality.
    16
    Check fruit quality from an IoT device
    Learn about using your fruit quality detector from an IoT device.
    17
    Run your fruit detector on the edge
    Learn about running your fruit detector on an IoT device on the edge.
    18
    Trigger fruit quality detection from a sensor
    Learn about triggering fruit quality detection from a sensor.
    Retail
    19
    Train a stock detector
    Learn how to use object detection to train a stock detector to count stock in a shop.
    20
    Check stock from an IoT device
    Learn how to check stock from an IoT device using an object detection model.
    Consumer
    21
    Recognize speech with an IoT device
    Learn how to recognize speech from an IoT device to build a smart timer.
    22
    Understand language
    Learn how to understand sentences spoken to an IoT device.
    23
    Set a timer and provide spoken feedback
    Learn how to set a timer on an IoT device and give spoken feedback on when the timer is set and when it finishes.
    24
    Support multiple languages
    Learn how to support multiple languages, both being spoken to and the responses from your smart timer.
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