Online or onsite, instructor-led live microcontroller training courses demonstrate through hands-on practice how to set up and program microcontrollers for use in controlling real-world devices such as lights, motors and motion detection sensors. Microcontrollers can also be used as complete server systems for dedicated tasks such as printing and web serving.
Microcontroller training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Microcontroller training can be carried out locally on customer premises in Arizona or in NobleProg corporate training centers in Arizona.
Learn Microcontroller in our training center in Arizona.
The office in Phoenix's 24th at Camelback is located at the city's most prestigious address and provides stunning views of Camelback Mountain and the downtown Phoenix skyline. Conveniently placed at the crossing of major transport links, it features a secure underground parking as well as a beautiful courtyard.
Learn Microcontroller in our training center in Arizona. The center is conveniently located in downtown Phoenix and in just walking distance to numerous restaurants, shops, and businesses.
Only few minutes away from Metro Light Rail and 15 minutes drive from Phoenix Sky Harbor International Airport.
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Learn Microcontroller in our training center in Arizona.
Experience a professional, modern workspace at the Region’s Center office at 400 West Capitol Avenue in the heart of downtown Little Rock. The center is ideally located off South Broadway with fast access to I-630 and the Bill and Hillary Clinton National Airport. The tower features an array of onsite amenities including a bank, gift store, pharmacy and more for your convenience. Our clients may enjoy our classic American food at Franke’s Cafeteria onsite or...
I enjoyed the training was delivered by someone with experience in the field.
Nicholas Scott - University of Glasgow
Course: Arduino: Programming a Microcontroller for Beginners
The aquisition of useful knowlwdge and clarification of some things I was not sure of peviously.
Kenneth Mahoney - University of Glasgow
Course: Arduino: Programming a Microcontroller for Beginners
Rod seemed very knowledgeable and enthusiastic about the course material.
Kyle Stirling - University of Glasgow
Course: Arduino: Programming a Microcontroller for Beginners
2 days of no interptions, which enabled me to concentrate on the task in hand.
University of Glasgow
Course: Arduino: Programming a Microcontroller for Beginners
I found the balance of "white board" teaching versus practical "hands-on" learning was just right for an Arduino introductory course, and the pace was also appropriate.
Neil Owen - University of Glasgow
Course: Arduino: Programming a Microcontroller for Beginners
I already had a little knowledge of Arduino, so it was good to hear more about the background of arduino, what it can be used for, and the resources available for help.
University of Glasgow
Course: Arduino: Programming a Microcontroller for Beginners
Rod's style was entertaining.
Tom O'Hara - University of Glasgow
Course: Arduino: Programming a Microcontroller for Beginners
relaxed and informal environment plenty of help during worked examples
bernard hoey - University of Glasgow
Course: Arduino: Programming a Microcontroller for Beginners
This instructor-led, live training in Arizona (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).
In this instructor-led, live training in Arizona, 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.
This instructor-led, live training in Arizona (online or onsite) is aimed at engineers who wish to learn the design principles of microcontroller design.
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.
This instructor-led, live training in Arizona (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.
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