LLMs in Multimodal Applications Training Course
The integration of different types of data such as text, image, and audio represents the forefront of LLM applications, enabling more comprehensive and context-aware AI systems.
This instructor-led, live training (online or onsite) is aimed at intermediate-level data scientists, machine learning engineers, and software developers who wish to apply Large Language Models (LLMs) to multimodal data for advanced AI applications.
By the end of this training, participants will be able to:
- Understand the principles of multimodal learning with LLMs.
- Implement LLMs to process and analyze text, image, and audio data.
- Develop applications that leverage the strengths of multimodal data integration.
- Evaluate the performance of multimodal LLM systems.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
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Course Outline
Introduction to Multimodal Learning
- Overview of multimodal AI
- Challenges in multimodal data processing
- Benefits of multimodal LLMs
Understanding Large Language Models
- Architecture of state-of-the-art LLMs
- Training LLMs with multimodal data
- Case studies: Successful multimodal LLM applications
Processing Multimodal Data
- Data preprocessing techniques for text, image, and audio
- Feature extraction and representation learning
- Integrating multimodal data in LLMs
Developing Multimodal LLM Applications
- Designing user interfaces for multimodal interaction
- LLMs in virtual assistants and chatbots
- Creating immersive experiences with LLMs
Evaluating and Optimizing Multimodal Systems
- Performance metrics for multimodal LLMs
- Optimization strategies for better accuracy and efficiency
- Addressing bias and fairness in multimodal systems
Hands-on Lab: Building a Multimodal LLM Project
- Setting up a multimodal dataset
- Implementing a multimodal LLM for a specific use case
- Testing and refining the system
Summary and Next Steps
Requirements
- An understanding of machine learning and neural networks
- Experience with Python programming
- Familiarity with data preprocessing for various data types (text, image, audio)
Audience
- Data scientists
- Machine learning engineers
- Software developers
- Researchers focusing on AI and natural language processing
14 Hours
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 3200 € + VAT*
Contact us for an exact quote and to hear our latest promotions
(*The final price may vary depending on the technical specialization of the course, the level of customization, the method of delivery and the number of learners)
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