LLMs in Multimodal Applications Training Course
The integration of diverse data types, including text, images, and audio, represents the forefront of Large Language Model (LLM) applications. This approach enables more comprehensive and context-aware artificial intelligence systems that can better serve various sectors, including those for government.
This instructor-led, live training (available online or onsite) is designed for intermediate-level data scientists, machine learning engineers, and software developers who aim to apply LLMs to multimodal data for advanced AI applications in public sector workflows.
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 effectively.
- Develop applications that leverage the strengths of multimodal data integration for government and other sectors.
- Evaluate the performance and reliability of multimodal LLM systems in alignment with public sector governance and accountability standards.
Format of the Course
- Interactive lecture and discussion tailored to public sector needs.
- Lots of exercises and practical applications relevant to government workflows.
- Hands-on implementation in a live-lab environment, focusing on real-world scenarios for government use.
Course Customization Options
- To request a customized training for this course, particularly tailored for government agencies, please contact us to arrange.
Course Outline
Introduction to Multimodal Learning
- Overview of Multimodal Artificial Intelligence (AI)
- Challenges in Processing Multimodal Data
- Benefits of Multimodal Large Language Models (LLMs) for Government
Understanding Large Language Models
- Architecture of State-of-the-Art LLMs
- Training LLMs with Multimodal Data
- Case Studies: Successful Applications of Multimodal LLMs in Public Sector Operations
Processing Multimodal Data
- Data Preprocessing Techniques for Text, Image, and Audio
- Feature Extraction and Representation Learning
- Integrating Multimodal Data into LLMs for Government Use
Developing Multimodal LLM Applications
- Designing User Interfaces for Multimodal Interaction in Government Services
- Leveraging LLMs in Virtual Assistants and Chatbots for Government
- Creating Immersive Experiences with LLMs for Enhanced Public Engagement
Evaluating and Optimizing Multimodal Systems
- Performance Metrics for Multimodal LLMs in Government Applications
- Optimization Strategies for Improved Accuracy and Efficiency in Government Operations
- Addressing Bias and Fairness in Multimodal Systems for Government Use
Hands-on Lab: Building a Multimodal LLM Project for Government
- Setting Up a Multimodal Dataset for Government Applications
- Implementing a Multimodal LLM for a Specific Use Case in Government
- Testing and Refining the System to Meet Government Standards
Summary and Next Steps
Requirements
- An understanding of machine learning and neural networks for government applications
- Experience with Python programming
- Familiarity with data preprocessing techniques for various data types (text, image, audio)
Audience
- Data scientists working in public sector roles
- Machine learning engineers supporting government projects
- Software developers focused on governmental technology solutions
- Researchers concentrating on AI and natural language processing for government use
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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