Building Conversational AI Applications Training
Course Authors
Building Conversational AI Applications Training Hands-on (Online, Onsite, and Classroom Live)
| Commitment | 1 Day, 7-8 hours a day. |
| Language | English |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | REQUEST |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
With Building Conversational AI Applications Training, participants will learn to build and deploy a real-time telemedicine application with transcription and named entity recognition capabilities.
This course is part of the following Certifications:
- NVIDIA-Certified Associate: Generative AI LLMs
Please note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be canceled, and no refund will be issued, regardless of attendance.
WHAT'S INCLUDED?
- 1 day of Building Conversational AI Applications Training with an expert instructor
- Building Conversational AI Applications Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- Building Conversational AI Applications – https://www.wiley.com/
- Building Conversational AI Applications – https://www.packtpub.com/
- Building Conversational AI Applications – https://store.logicaloperations.com/
- Building Conversational AI Applications – https://us.artechhouse.com/
- Building Conversational AI Applications Training – https://www.amazon.com/
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ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completion of this Building Conversational AI Applications Training course, participants can:
- How to customize and deploy ASR and TTS models on Riva.
- How to build and deploy an end-to-end conversational AI pipeline, including ASR, NLP, and TTS models, on Riva.
- How to deploy a production-level conversational AI application with a Helm chart for scaling in Kubernetes clusters.
CUSTOMIZE IT
- We can adapt this Building Conversational AI Applications Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this Building Conversational AI Applications course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the Building Conversational AI Applications course around the mix of technologies of interest to you (including technologies other than those in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policymaker), and present the Building Conversational AI Applications course in a manner understandable to lay audiences.
AUDIENCE/TARGET GROUP
The target audience for this Building Conversational AI Applications course:
- ALL
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this Building Conversational AI Applications Training course are:
- N/A
COURSE SYLLABUS
Introduction
- Meet the instructor.
- Create an account at courses.nvidia.com/join
Introduction to Conversational AI
- Explore the conversational AI landscape and gain a deeper understanding of the key components of ASR pipelines:
- Work through an ASR model example from audio to spectrogram to text.
- Explore decoders, customizations, and additional models, including inverse text normalization (ITN), punctuation and capitalization, and language identification.
- Deploy Riva ASR.
Customized Conversational AI Pipelines
- Explore the key components of the TTS pipeline and full pipeline customizations:
- Explore the spectrogram generator model and the vocoder model.
- Work with text normalization and grapheme to phoneme (G2P) conversion to customize pronunciations.
- Deploy a full ASR-NLP-TTS custom pipeline in Riva.
Inference and Deployment Challenges
- Explore challenges related to performance, optimization, and scaling in production deployment of conversational AI applications:
- Gain an understanding of the inference deployment process.
- Analyze non-functional requirements and their implications.
- Use a Helm chart to deploy a conversational AI application with a Kubernetes cluster.
Final Review
- Review key learnings and answer questions.
- Complete the assessment and earn a certificate.
- Complete the workshop survey.
- Learn how to set up your own AI application development environment.
