Developing AI Inference Solutions with the Vitis AI Platform

This course describes how to use the Vitis™ AI development platform in conjunction with DNN algorithms, models, inference and training, and frameworks on cloud and edge computing platforms.

Learn more about the Vitis Unified Software Platform from AMD Xilinx.

See Course Outline

2-Day Instructor-led CoursePrice USDTraining Credits
Hosted Online - $299/day$5986
In-Person Registration - $399/day$7988
Printed Course Book (A PDF book is included in the course fee)$1001
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Scheduled Classes

No Scheduled Sessions - Contact Us to ask about setting one up!

View our Full Calendar for class date status.
(Confirmed, Closed, Full)

Training Duration:

2 Days

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Who should attend:

Software and hardware developers, AI/ML engineers, data scientists, and anyone who needs to accelerate their software applications using AMD Xilinx devices.

Skills Gained

After completing this comprehensive training, you will know how to:

  • Describe AMD Xilinx machine learning solutions with the Vitis AI development platform and environment
  • Describe the supported frameworks, network modes, and pre-trained models for cloud and edge applications
  • Utilize DNN algorithms, models, inference and training, and frameworks on cloud and edge computing platforms
  • Use the Vitis AI quantizer and AI compiler to optimize a trained model
  • Use the architectural features of the DPU processing engine to optimize a model for an edge application
  • Identify the high-level libraries and APIs that come with the AMD Xilinx Vitis AI Library
  • Create a custom hardware overlay based on application requirements
  • Create a custom application using a custom hardware overlay and deploy the design

Course Outline

Day 1Day 2
  • Introduction to the Vitis AI Development Environment {Lecture}
  • Overview of ML Concepts {Lecture}
  • Frameworks Supported by the Vitis AI Development Environment {Lecture}
  • Setting Up the Vitis AI Development Environment {Demo}
  • AI Optimizer {Lecture}
  • AI Quantizer and AI Compiler {Lecture, Lab}
  • AI Profiler and AI Debugger {Lecture}
  • Introduction to the Deep Learning Processor Unit (DPU) {Lecture}
  • DPUCADX8G Architecture Overview {Lecture}
  • DPUCZDX8G Architecture Overview {Lecture}
  • Vitis AI Library {Lecture, Labs}
  • Creating a Custom Hardware Platform with the DPU Using the Vivado Design Suite Flow (Edge) {Lab}
  • Creating a DPU Kernel Using the Vitis Environment Flow (Edge) {Lab}
  • Creating a Vitis Embedded Acceleration Platform (Edge) {Lecture}
  • Creating a Custom Application (Edge) {Lab}

Please note: The instructor may change the content order to provide a better learning experience.


  • Basic knowledge of machine learning concepts
  • Deep learning frameworks (such as TensorFlow, Pytorch, and Caffe)
  • Comfort with the C/C++/Python programming language
  • Software development flow


Updated 11-13-2023
©2023 Advanced Micro Devices, Inc. Xilinx, Inc. is now part of AMD. Xilinx, the Xilinx logo, AMD, the AMD Arrow logo, Alveo, Artix, Kintex, Kria, Spartan, Versal, Vitis, Virtex, Vivado, Zynq, and other designated brands included herein are trademarks of Advanced Micro Devices, Inc.