Microcontroller Training Courses

Microcontroller Training Courses

I corsi di formazione sul microcontrollore live con istruttore locale dimostrano attraverso la pratica del handson come impostare e programmare i microcontrollori da utilizzare nel controllo di dispositivi realworld come luci, motori e sensori di rilevamento del movimento I microcontrollori possono anche essere utilizzati come sistemi server completi per attività dedicate come la stampa e la web serving La formazione sui microcontrollori è disponibile come "allenamento dal vivo in loco" o "allenamento dal vivo a distanza" La formazione on-site in loco può essere svolta localmente presso la sede del cliente in Italia o nei centri di formazione aziendale NobleProg in Italia La formazione in remoto dal vivo viene effettuata tramite un desktop remoto interattivo NobleProg Il tuo fornitore di formazione locale.

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Schema generale del corso Microcontroller

Nome del corso
Durata
Overview
Nome del corso
Durata
Overview
21 hours
Overview
In this instructor-led, live training in Italia, participants will learn how to program the Arduino for real-world usage, such as to control lights, motors and motion detection sensors. This course assumes the use of real hardware components in a live lab environment (not software-simulated hardware).

By the end of this training, participants will be able to:

- Program Arduino to control lights, motors, and other devices.
- Understand Arduino's architecture, including inputs and connectors for add-on devices.
- Add third-party components such as LCDs, accelerometers, gyroscopes, and GPS trackers to extend Arduino's functionality.
- Understand the various options in programming languages, from C to drag-and-drop languages.
- Test, debug, and deploy the Arduino to solve real world problems.
14 hours
Overview
Raspberry Pi is a very small, single-board computer.

In this instructor-led, live training, participants will learn how to set up and program the Raspberry Pi to serve as an interactive and powerful embedded system.

By the end of this training, participants will be able to:

- Set up an IDE (integrated development environment) for maximum development productivity
- Program Raspberry Pi to control devices such as motion sensor, alarms, web servers and printers.
- Understand Raspberry Pi's architecture, including inputs and connectors for add-on devices.
- Understand the various options in programming languages and operating systems
- Test, debug, and deploy the Raspberry Pi to solve real world problems

Audience

- Developers
- Hardware/software technicians
- Technical persons in all industries
- Hobbyists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Note

- Raspberry Pi supports various operating systems and programming languages. This course will use Linux-based Raspbian as the operating system and Python as the programming language. To request a specific setup, please contact us to arrange.
- Participants are responsible for purchasing the Raspberry Pi hardware and components.
35 hours
Overview
Questa formazione dal vivo con istruttore (in loco o remoto) è rivolta agli ingegneri che desiderano apprendere i principi di progettazione del microcontrollore.

Formato del corso

- Conferenza e discussione interattiva.
- Molti esercizi e pratiche.
- Implementazione pratica in un ambiente live-lab.

Opzioni di personalizzazione del corso

- Per richiedere una formazione personalizzata per questo corso, ti preghiamo di contattarci per organizzare.
35 hours
Overview
This instructor-led, live training in Italia (online or onsite) is aimed at engineers who wish to learn how to use embedded C to program various types of microcontrollers based on different processor architectures (8051, ARM CORTEX M-3, and ARM9).
21 hours
Overview
This instructor-led, live training in Italia (online or onsite) is aimed at engineers who wish to write, load and run machine learning models on very small embedded devices.

By the end of this training, participants will be able to:

- Install TensorFlow Lite.
- Load machine learning models onto an embedded device to enable it to detect speech, classify images, etc.
- Add AI to hardware devices without relying on network connectivity.

Prossimi corsi Microcontroller

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