Learn About and AI with Intel to Boost Your Career

Learn About and AI with Intel to Boost Your Career

About Course

Leverage the Intel® Distribution of OpenVINO™ Toolkit to fast-track development of high-performance computer vision and deep learning inference applications, and run pre-trained deep learning models for computer vision on-premise. You will identify key hardware specifications of various hardware types (CPU, VPU, FPGA, and Integrated GPU), and utilize the Intel® DevCloud for the Edge to test model performance on the various hardware types. Finally, you will use software tools to optimize deep learning models to improve the performance of Edge AI systems.


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Prerequisite Knowledge 

Edge AI Fundamentals with OpenVINO

Leverage a pre-trained model for computer vision inferencing. You will convert pre-trained models into the framework-agnostic intermediate representation with the Model Optimizer, and perform efficient inference on deep learning models through the hardware-agnostic Inference Engine. Finally, you will deploy an app on the edge, including sending information through MQTT, and analyze model performance and use cases

 

Hardware for Computer Vision & Deep Learning Application Deployment

Grow your expertise in choosing the right hardware. Identify key hardware specifications of various hardware types (CPU, VPU, FPGA, and Integrated GPU). Utilize the Intel® DevCloud for the Edge to test model performance and deploy power-efficient deep neural network inference on the various hardware types. Finally, you will distribute the workload on available computing devices in order to improve model performance.

 

Optimization Techniques and Tools for Computer Vision & Deep Learning Applications

Learn how to optimize your model and application code to reduce inference time when running your model at the edge. Use different software optimization techniques to improve the inference time of your model. Calculate how computationally expensive your model is. Use the DL Workbench to optimize your model and benchmark the performance of your model. Use a VTune amplifier to find and fix hotspots in your application code. Finally, package your application code and data so that it can be easily deployed to multiple devices.

 
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All Their Programs Include

Real-world projects from industry experts

With real-world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want

Technical mentor support

Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

Personal career coach and career services
You’ll have access to career coaching sessions, interview prep advice, and resume and online professional profile reviews to help you grow in your career.

Flexible learning program

Get a custom learning plan tailored to fit your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.



WHY SHOULD YOU ENROLL FOR THIS PROGRAM

70% of data being created is at the edge, and only half of that will go to the public cloud; the rest will be stored and processed at the edge, which requires a different kind of developer. Demand for professionals with the Edge AI skills will be immense, as the Edge Artificial Intelligence (AI) software market size is forecasted to grow from $355 Million in 2018, to $1.15 billion by 2023, at an Annual Growth Rate of 27%.(MarketsandMarkets) In the Edge AI for IoT Developers Nanodegree program, you'll leverage the potential of edge computing and use the Intel® Distribution of OpenVINO™ Toolkit to fast-track development of high-performance computer vision and deep learning inference applications.