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Ultra96 Technical Training Courses

14 Jan 2020 - 31 Dec 2020

Multiple Locations

Developing Zynq UltraScale+ MPSoC Software, with Xilinx Software Development Kit 2018.3

This course explores the basic fundamentals in the Xilinx Software Development Kit (SDK). Using a pre-built hardware platform, you will learn how to navigate the SDK environment and develop some basic C-code examples for the Ultra96 / Ultra96-V2 board.


  • Introduce developers to the Xilinx SDK
  • Explore how to import hardware into your Xilinx SDK environment
  • Connect the SDK to hardware for execution and debug
  • Utilize a peripheral interrupt to show real-time software response
  • Show a basic example of how to use an external sensor module


Developing Zynq UltraScale+ MPSoC Hardware, with Xilinx Vivado 2018.3

This course will teach you how to develop a Zynq UltraScale+ MPSoC hardware platform using the Xilinx Vivado tools while also learning the ZU+ architecture. Vivado is used to configure the processing system parameters, including clocking, memory interface, and peripherals. Vivado is also used to develop custom hardware in the programmable logic. Build a working hardware platform that runs your code on the Ultra96 / Ultra96-V2 board.


  • Introduction to the Zynq UltraScale+ MPSoC development flow with Vivado’s IP Integrator
  • Introduction to the Zynq UltraScale+ MPSoC Architecture including the ARM Cortex™-A53 Processor
  • Utilize the Xilinx embedded systems tools to
    • Design a Zynq UltraScale+ MPSoC system
    • Add Xilinx and custom IP
    • Run software applications to test the IP
    • Debug an embedded system


  • Developing Zynq UltraScale+ MPSoC Software course or applicable experience


Integrating Sensors on Ultra96 with PetaLinux 2018.3

From within an Ubuntu OS running within a virtual machine, learn how to install PetaLinux and build embedded Linux targeting Ultra96 or Ultra96-V2. In the hands-on labs learn about Yocto and PetaLinux tools to import your own FPGA hardware design, integrate user space applications, and configure/customize PetaLinux.


  • Build, customized and configure PetaLinux for Ultra96
  • Import existing Vivado hardware designs into PetaLinux
  • Add custom applications into PetaLinux


  • Developing Zynq UltraScale+ MPSoC Software course or applicable experience


Avnet hardware required to complete the labs for all Introductory Courses
- Ultra96 Development Board (AES-ULTRA96-G or AES-ULTRA96-V2-G) $249.00
- Ultra96 USB-JTAG/UART Pod (AES-ACC-U96-JTAG) $39.00
- Power Supply (AES-ACC-U96-4APWR) $19.99
- Click Mezzanine Bundle (AES-ACC-U96-ME-SK) $49.00


Attendees also need the following

- Laptop with Ubuntu Virtual Machine with Xilinx SDSoC 2018.3 Suite installed

- Micro-USB cable (Example: 83-16412 - USB Cable, USB Type A Plug, Micro USB Type B)

- USB-to-SD Card reader is highly recommended (GFR304SD - Card Reader/Writer, USB 3.0, SD/MicroSD)

A Practical Guide to Getting Started with Xilinx SDSoC 2018.3

Using proven flows for SDSoC, you will learn how to navigate SDSoC. On the first day, through hands-on labs, we will create a design for a provided platform and then also create a platform for the Avnet Ultra96. You will see how to accelerate an algorithm in the course lab. On the second day, a similar workflow is taken.  This time focusing on PetaLinux integration, while leveraging the knowledge we built from the first day.  This experience should give you the background to assist you in developing custom platforms with custom algorithms, accelerated by SDSoC.


  • Introduction to the design concepts and problem-solving techniques of SDSoC
  • Build the bare metal platform from scratch
  • Enable and test a PetaLinux BSP running on the Ultra96 Development Board
  • Test the platform using a simple Matrix Multiplier


  • A working knowledge of Xilinx Vivado, SDK, and PetaLinux design tools and flow
  • Or, attendance at our other three fundamentals courses (live or on-demand)   
  • Experience with the v2018.3 tools is recommended but not required


Introduction to Deep Learning with Xilinx SoCs

Deep learning achieves human-like accuracy for many tasks considered algorithmically unsolvable with traditional machine learning. It is frequently used to develop applications such as face recognition, automated driving, and image classification.

Introduction to Deep Learning with Xilinx SoCs is a two-day technical training course that provides a hands-on introduction to deep learning, from training to inference.  The Deep Learning toolbox from the MathWorks is used to provide an interactive introduction to deep learning, including workflows for creating and training Deep Neural Networks (DNN) from scratch, as well as with transfer learning.  The Xilinx Edge AI Inference solution is used to deploy the DNN for inference on the Xilinx MPSoC (Ultra96).


Day 1 - Deep learning overview and training with MathWorks

  • Use pre-trained DNNs for image classification
  • Manage collections of data for deep learning
  • Create and train a DNN from scratch for digit classification
  • Use transfer learning to modify a pre-trained network to classify images into specified classes

Day 2 - Deep learning inference on Xilinx SoCs

  • Overview of Xilinx's AI inference solutions, from cloud to edge
  • Deep dive into the development flow for Xilinx edge AI platforms
  • Quantize, compile, and deploy DNNs to the Ultra96


  • PetaLinux Tools for Ultra96 Development or applicable experience


Turbocharge Python with Ultra96 PYNQ

Take Python to the next level with PYNQ and the Avnet / Xilinx Ultra96 hardware platform.  PYNQ is an open source Python productivity framework for Xilinx MPSoC that comes integrated with AArch64 Linux based on Ubuntu 18.04 LTS.  Ultra96 is a 96Boards certified palm of your hand computing platform designed around the high-performance Xilinx MPSoC ZU3EG.  The ZU3EG has 6 Arm™ CPUs, display port, multiple peripherals and programmable logic.


  • Accelerate Python with hardware
  • Control hardware with Python
  • Develop applications for Ultra96 with a web browser based IDE: Jupyter Labs
  • Re-use open source based projects with Ultra96
  • Write custom drivers completely in Python to interface with Xilinx programmable logic
  • Create living-code documents with Jupyter Notebooks
  • Working examples will include:  Machine learning image classification, hardware accelerated OpenCV and more...


  • Some knowledge of Python 3 is necessary
  • For serious beginners, a highly recommended book is: “Python Crash Course: A Hands-On, Project-Based Introduction to Programming”
  • An excellent 1-hour free intro to Python course can also be found here:  https://youtu.be/tBCdvX8MSRc
  • General Linux experience, Xilinx hardware design skills and understanding of C programming will help make more sense of the course but are not required


Avnet hardware required for Advanced Courses
- Ultra96 Development Board (AES-ULTRA96-G or AES-ULTRA96-V2-G) $249.00
- Ultra96 USB-JTAG/UART Pod (AES-ACC-U96-JTAG) $39.00
- Power Supply (AES-ACC-U96-4APWR) $19.99


Attendees also need the following

- Laptop with Xilinx Vivado Design Suite 2018.3 installed
- Micro-USB cable (Example: 83-16412 - USB Cable, USB Type A Plug, Micro USB Type B)


For the Deep Learning course attendees will also need

- Laptop with Linux Virtual Machine installed
- Xilinx SDSoC Design Suite 2018.3 installed under Linux
- USB-to-SD Card reader is highly recommended (GFR304SD - Card Reader/Writer, USB 3.0, SD/MicroSD)
- USB camera, one of the following recommended:

  • Logitech BRIO
  • Logitech C920
  • Logitech C270





Training Course Bundle $59.

Hardware required to complete course. Purchase: Required hardware for Ultra96 courses



Take the courses online at Hackster.io



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Secure ROI of your IoT Solution with Embedded Computing

15 Oct 2020 - 31 Dec 2020

Join Avnet experts for a webinar on how embedded computing affects ROI in IoT solution development. You'll leave with a better understanding of how important it is to select the right embedded computing technology to avoid hidden costs.

Road with streams of light from moving cars

Capacitive touch controls boost automotive circuit reliability

13 Oct 2020 - 13 Oct 2021
On Demand

Many automotive applications require some degree of reliable human control. While capacitive touch controls are more reliable and safer than mechanical switches, they are also subject to EMI interference. Join engineers from Avnet and ON Semiconductor in a free-wheeling discussion on capacitive touch controls for cars and how to make them road-ready.

Avnet's RFSoC Explorer for MATLAB and Simulink

Verify Xilinx RFSoC Gen-3 System Performance in mmWave Applications

29 Sep 2020 - 29 Sep 2021

Avnet and MathWorks engineers will demonstrate how to capture, measure and characterize RF performance in millimeter-wave bands using MATLAB and Simulink and the Avnet mmWave Radio Development Kit with Xilinx Zynq UltraScale+ RFSoC Gen-3.