Online or onsite, instructor-led live OpenVINO training courses demonstrate through interactive hands-on practice how to use OpenVINO toolkit for optimizing Deep Learning models on Intel hardware.
OpenVINO 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 OpenVINO training can be carried out locally on customer premises in Nepal or in NobleProg corporate training centers in Nepal.
NobleProg -- Your Local Training Provider
Nepal, Kathmandu - Classroom
near Soaltee, Tahachal Marg, Kathmandu, Nepal, 44600
Set in Kathmandu, this classroom is well located near Tahachal Marg with all amenities and WiFi.
For Sales Enquires and Meetings
All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
Nepal, Thamel, KTM - Classroom
near Radisson , Ward 2, Kathmandu, Nepal, 44600
Set in Kathmandu, this classroom is well located near Thamel, with all amenities and WiFi.
For Sales Enquires and Meetings
All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
This instructor-led, live training in Nepal (online or onsite) is aimed at data scientists who wish to accelerate real-time machine learning applications and deploy them at scale.
By the end of this training, participants will be able to:
Install the OpenVINO toolkit.
Accelerate a computer vision application using an FPGA.
Execute different CNN layers on the FPGA.
Scale the application across multiple nodes in a Kubernetes cluster.
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