With ChatGPT, other large language models and generative AI have caught the attention of global consumers, enterprises, and C-suites.

AI has a big role to play in the enterprise space and it is progressing rapidly. Without understanding the concepts behind these advanced technologies, developers and administrators will struggle to evaluate the potential impact of new tools and solutions.

A multimodal GenAI application seamlessly generates high-quality content across text, images, video, and audio, all at once. Such applications would more accurately capture the multimodal nature of the world and human comprehension, seamlessly consolidate information from a wide range of sources, and enable strong immersion in human-AI interactions. This could transform the way humans interact with computers on various tasks, including assistive technology, custom learning tools, ambient computing, and content generation.

Azure OpenAI Service provides REST API access to OpenAI's powerful language models including the GPT-3, GPT-4, Codex and Embeddings model series and DALL-E. These models can be easily adapted to your specific task including but not limited to content generation, summarization, semantic search, and natural language to code translation. Users can access the service through REST APIs, Python SDK, or our web-based interface in the Azure OpenAI Studio.

Microsoft Azure AI lets you build apps with powerful algorithms to see, hear, speak, understand, and interpret our needs using natural methods of communication, with just a few lines of code. Easily add intelligent features – such as emotion and sentiment detection, vision and speech recognition, language understanding, knowledge, and search – into your app, across devices and platforms such as iOS, Android, and Windows, keep improving and are easy to set up. Containerization lets developers build big AI systems that run at scale, reliably, and consistently in a way that supports better data governance.

In this 4-day virtual hands-on workshop, Microsoft AI and Business Applications MVP and Microsoft Certified Trainer Prashant G Bhoyar will cover the following topics in detail:

• What are Multimodal GenAI Applications?
• Azure OpenAI Services: We will explore what these services are, their architecture, and their place within the broader AI ecosystem.
• Azure OpenAI Studio: An in-depth overview of the Azure OpenAI Studio.
• Prompt Engineering: An in-depth look at this critical aspect of large language model usage. We will cover how prompts work, why they are important, and the factors that influence their effectiveness.
• Use Case and Common Architecture: Hands-on labs covering the use case and common architecture of the implementation
• Azure OpenAI Service Embedding Models
• Semantic Kernel is an open-source SDK that lets you easily combine AI services like OpenAI, Azure OpenAI, and Hugging Face with conventional programming languages like C# and Python. By doing so, you can create AI apps that combine the best of both worlds.
• Microsoft Copilot Studio lets you create powerful AI-powered copilots for a range of requests—from providing simple answers to common questions to resolving issues requiring complex conversations. Engage with customers and employees in multiple languages across websites, mobile apps, Facebook, Microsoft Teams, or any channel supported by the Azure Bot Framework.
• Customizing Azure OpenAI Services: From configuration to deployment, we'll show you how to tailor these services to suit a range of specific needs.
• Deep dive into Azure OpenAI Services: We'll specifically focus on several of the models like GPT, Ada, and DALL-E, discussing their unique features and optimal use cases.
• Using Azure OpenAI Service to access company data
• Azure AI Services Overview: Discussion on key components such as Language Services, Speech services, Vision services, and their real-world applications.
• Conversational AI: A look at the development of AI that can engage in human-like dialogues, including designing, training, and refining conversational models.
• Azure AI Search: We will cover how we can use this service to create an advanced search experience.
• Document Intelligence Service: We will cover how this service uses machine learning technology to identify and extract key-value pairs and table data from form documents.
• A thorough examination of the AutoGen Framework and its capabilities.
• Responsible AI
• Creating Enterprise-Level Applications: Practical guidance on developing robust, scalable applications using Azure OpenAI, ChatGPT, and Azure AI Services, focusing on industry requirements and best practices.

At the end of the workshop, attendees will have a working knowledge of how to build next-gen multimodal applications and custom Copilots with Azure OpenAI and Cognitive Services.

Access to Azure and Azure OpenAI services will be provided to follow the labs and create enterprise-grade multimodal applications. The labs will be a mixture of Python and C#.

You will learn:

• About Multimodal GenAI Applications
• How to use Case and Common Architecture with hands-on labs covering the use case and common architecture of the implementation
• How to create enterprise-level appplications with Practical guidance on developing robust, scalable applications using Azure OpenAI, ChatGPT, and Azure AI Services, focusing on industry requirements and best practices

Attendee Workstation Requirements:
You must provide your own computer (Windows or Mac) for this hands-on lab seminar with a camera, wired Internet connection, speakers, and a microphone - tablets will not work for this workshop. The following technologies must be installed on the computer prior to the start of the Seminar:

• A modern browser like Microsoft Edge, Google Chrome, Firefox, Safari
• Your computer must have the ability to run C# 10 code or Python: (One of Visual Studio 2022/VSCode 1.66+/VSMac/Rider/etc.) and also must be able to access www.azure.com.
• Access to Azure and Azure OpenAI services will be provided to follow the labs and create enterprise-grade intelligent applications. However, attendees are encouraged to use their own Azure subscription. The labs will be a mixture of Python and C#.