Multi-Modal AI Agents Training in Australia

This course introduces participants to the design, development, and deployment of multi-modal AI agents that can interact and reason across text, images, and speech. It covers foundational concepts, tools, and frameworks for building real-world intelligent systems capable of natural communication, understanding, and decision-making across multiple data modalities.

Welcome to the official Multi-Modal AI Agents Training certification program. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge in in Australia. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 21 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

• Basic knowledge of Python programming

• Familiarity with Machine Learning and Deep Learning fundamentals

• Understanding of Natural Language Processing (NLP) basics

• Exposure to frameworks like TensorFlow or PyTorch (recommended but not mandatory)

• Prior experience with AI/ChatGPT helpful but not required

• Multi-modal AI development (text, vision, speech integration)

• Agent architecture design and orchestration

• Prompt engineering for multi-modal contexts

• Model fine-tuning for custom tasks

• AI tool integration (LangChain, RAG, vector databases, OpenAI GPT-4V, Speech APIs, etc.)

• Real-world deployment of intelligent systems

By the end of the course, participants will be able to:

1. Understand the principles of multi-modal learning and integration.

2. Build AI agents that process and combine text, images, and speech data.

3. Use popular frameworks and APIs (OpenAI, Hugging Face, LangChain, etc.) for multi-modal AI development.

4. Develop business and domain-specific applications of multi-modal AI agents.

5. Deploy AI agents for automation, customer experience, and advanced decision-making.