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Duration 21 hours
Course Outline
Introduction to Multimodal AI and Ollama
- Fundamentals of multimodal learning
- Primary challenges in integrating vision and language
- Exploring the capabilities and architecture of Ollama
Establishing the Ollama Environment
- Installation and configuration of Ollama
- Managing local model deployment
- Connecting Ollama with Python and Jupyter environments
Handling Multimodal Inputs
- Integrating text and image data
- Incorporating audio and structured information
- Architecting effective preprocessing pipelines
Applications in Document Understanding
- Extracting structured data from PDFs and images
- Combining OCR technology with language models
- Creating intelligent document analysis workflows
Visual Question Answering (VQA)
- Setting up VQA datasets and performance benchmarks
- Training and assessing multimodal models
- Developing interactive VQA applications
Architecting Multimodal Agents
- Core principles of agent design with multimodal reasoning
- Synthesizing perception, language, and action
- Deploying agents for practical use cases
Advanced Integration and Optimization
- Fine-tuning multimodal models using Ollama
- Enhancing inference performance
- Addressing scalability and deployment strategies
Summary and Next Steps
Requirements
- A solid grasp of core machine learning principles
- Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow
- Working knowledge of natural language processing and computer vision
Target Audience
- Machine learning engineers
- AI researchers
- Product developers integrating vision and text-based workflows
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
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