TrainingData & analytics / Data & AINVIDIA-AGENTS-2
NVIDIA-AGENTS-2NVIDIA · authorised training
NVIDIA: Building AI Agents with Multimodal Models (English)
In this training, you will learn how to develop neural networks that combine different data types (from LiDAR scans to text extracted from documents) to enable better predictions and analyses. Participants explore fusion techniques and orchestration of multimodal models through practical examples such as video analysis.
- Duration
- 1 day
- Level
- Intermediate
- Provider
- NVIDIA
- Topic
- Data & analytics / Data & AI
Course outline
- Early and late fusion: combining camera and LiDAR data
- Intermediate fusion: designing architectures for multimodal networks
- Cross-modal projection: adapting language models for visual data (Vision Language Models, VLMs)
- Model orchestration: combining models to answer complex questions (e.g., video analysis with Cosmos Nemotron)
- Assessment: adapting a model to handle different input data
Skills you will gain
- Prepare data types for processing by neural networks
- Apply various fusion techniques (early, intermediate, late fusion)
- Extract text from PDF files using OCR
- Build and orchestrate simple multimodal models
- Independently adapt AI blueprints for practical applications such as video analysis
Who should attend
- Data Scientists
- AI Engineers
- Deep Learning Specialists
- Robotics Engineers
- Software developers working with neural networks
- Professionals working with sensor or imaging data who want to use AI for analysis and prediction
Prerequisites
- Basic knowledge of deep learning concepts
- Experience with a deep learning framework such as TensorFlow, PyTorch, or Keras (this training uses PyTorch)
Upcoming dates
These sessions run online with LLPA partners. Times are shown in Polish time, and the language of delivery is listed for each date.
| Date | Times (Polish time) | Language | Status | Price | Action |
|---|---|---|---|---|---|
| 09:30–16:30 | English | Scheduled | 3940 PLN | Request a quote |
3940 PLN
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