Building AI Agents with Multimodal Models
- Course Code GK847003
- Duration 1 day
Course Delivery
Course Delivery
This course is available in the following formats:
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Company Event
Event at company
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Virtual Learning
Learning that is virtual
Request this course in a different delivery format.
Course Overview
Top
Learn how to build neural network agents that reason across multiple data types using advanced fusion techniques, OCR, and NVIDIA AI Blueprints for real-world applications like robotics and healthcare.
Virtual Learning
This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.
Course Schedule
TopCourse Objectives
Top- In this course, you will learn about:
- Different data types and how to make them neural network ready
- Model fusion, and the differences between early, late, and intermediate fusion
- PDF extraction using OCR
- The difference between modality and agent orchestration
- Customization of NVIDIA AI Blueprints with Video Search and Summarization (VSS)
Course Content
TopModule 1: Early and Late Fusion
- Use camera and LiDAR data to predict object positions.
- Convert various datatypes to make them neural network ready.
Module 2: Intermediate Fusion
- Explore the theory behind effective multimodal model architecture.
- Train a Contrastive Pretraining model.
- Create a vector database.
Module 3: Cross-modal Projection
- Converting a Language model into a Vision Language Model (VLM).
- Process PDFs with Optical Character Recognition (OCR) tools.
Module 4: Model Orchestration
- Analyze video using Cosmos Nemotron.
- Use VSS to answer user queries about video content.
- Orchestrate with NVIDIA AI Blueprints.
Module 5: Assessment
- Convert a pre-trained model to input a different datatype using projection.
