Unable to find what you're searching for?
We're here to help you find itUnlock the potential of AI development with our AZ-2005: Develop AI Agents using Azure OpenAI and Semantic Kernel course. This 1-day intensive training immerses you in the practical use of the Semantic Kernel SDK to craft intelligent applications that excel in Natural language processing and task automation.
Through hands-on modules, you'll Build and optimize your kernel, Create custom plugins, and enhance your AI agent's skills. The course also covers practical methods for Combining prompts and functions, employing Intelligent planners, and concludes with a guided project to create an advanced AI travel agent.
Ideal for C# programmers familiar with Azure and Visual Studio Code, this course equips you with the expertise to develop cutting-edge AI solutions.
Purchase This Course
♱ Excluding VAT/GST
Classroom Training price is on request
You can request classroom training in any city on any date by Requesting More Information
♱ Excluding VAT/GST
Classroom Training price is on request
You can request classroom training in any city on any date by Requesting More Information
Sure, here are the minimum required prerequisites for successfully undertaking the AZ-2005: Develop AI Agents using Azure OpenAI and Semantic Kernel course:
Prerequisites:
These prerequisites ensure that you have the fundamental knowledge and tools to maximize your learning experience in this course. If you meet these requirements, you will be well-prepared to effectively learn how to use the Semantic Kernel SDK to build intelligent applications that automate tasks and perform natural language processing.
Introduction:
The AZ-2005 course teaches IT professionals to develop AI agents using Azure OpenAI and Semantic Kernel, focusing on automating tasks and natural language processing.
Job Roles/Audience:
In the AZ-2005: Develop AI Agents using Azure OpenAI and Semantic Kernel course, you will learn how to build intelligent applications that automate tasks and perform natural language processing using the Semantic Kernel SDK, within a single day.
Understand the purpose of Semantic Kernel: Learn the fundamental role and capabilities of the Semantic Kernel in building intelligent AI agents.
Master prompting basics: Gain knowledge on how to create effective prompts to interact with AI models proficiently.
Create effective prompts: Develop techniques to enhance the performance and accuracy of your prompts for better AI interactions.
Utilize Semantic Kernel plugins: Understand the functionality of premade plugins and how to incorporate them into your applications.
Develop custom plugins: Learn to design and implement your own plugins to extend the capabilities of the Semantic Kernel.
Implement native function skills: Grasp the concept of native functions within the Semantic Kernel SDK and how to create them.
Combine prompts with native functions: Discover how to integrate prompts and native functions to create more intelligent and dynamic AI responses.
Optimize and use planners: Understand and optimize the use of planners in the Semantic Kernel
Azure OpenAI is a cloud service provided by Microsoft Azure that integrates OpenAI's advanced AI models, like ChatGPT, to facilitate enhanced language understanding and generation. This platform offers a variety of AI tools that can interpret and generate human-like text, enabling developers to create sophisticated AI applications easily. Businesses can leverage Azure OpenAI to improve customer interaction, automate responses, and gain insights from data. As participants progress through the Azure AI certification path, such as the Azure AI-102 certification, they gain expertise in implementing AI solutions effectively using Azure's powerful AI capabilities.
AI development involves creating systems that can perform tasks usually requiring human intelligence. It includes machine learning, where computers learn from data to improve their performance over time. Azure AI is a set of services offered by Microsoft through its Azure platform, facilitating the building, training, and deploying of AI models. For professionals looking to specialize, the Azure AI certification path includes exams like Azure AI Fundamentals (AI-900) and Designing and Implementing an Azure AI Solution (AI-102) to validate skills in implementing AI solutions using Azure tools such as OpenAI and ChatGPT on Microsoft Azure.
Semantic Kernel SDK is a software development kit designed to enhance applications with natural language understanding capabilities. It allows developers to integrate advanced semantic processing features into their software, making it possible for applications to comprehend and interact with human language more effectively. This SDK is particularly useful in the development of AI-driven applications, where understanding the nuances of language is crucial for tasks such as sentiment analysis, topic extraction, and conversational AI. By leveraging the Semantic Kernel SDK, developers can create more intuitive and responsive applications that better serve user needs.
Natural language processing (NLP) is a branch of artificial intelligence that enables computers to understand, interpret, and generate human language. By analyzing and manipulating text, NLP technologies allow systems to perform tasks such as translating languages, responding to spoken commands, and summarizing large volumes of text. Advances in NLP have been integrated into various platforms, including Microsoft Azure, enhancing applications with capabilities ranging from automated customer support to intelligent document analysis. Azure AI offers specific certifications, like the Azure AI 102, to validate skills in implementing AI solutions, including NLP, using its cloud services.
Building and optimizing your kernel involves configuring and compiling the kernel of an operating system to enhance its performance and tailor it to your specific needs. This process requires a deep understanding of system architecture and the specific goals of your environment, whether it's to improve response time, handle large volumes of network traffic, or better manage hardware use. Optimization can lead to significant gains in efficiency and speed by stripping out unnecessary components and fine-tuning the kernel parameters to best suit the tasks your system handles most frequently.
Intelligent planners are advanced systems that use artificial intelligence to make decisions and solve complex problems efficiently. Integrating technologies such as Azure AI, these planners can analyze vast amounts of data, learn from past decisions, and predict outcomes. Whether used in logistics for route optimization or in project management for resource allocation, intelligent planners enhance decision-making processes and improve operational efficiency. Azure AI, including platforms like OpenAI and Azure, powers these planners, leveraging machine learning models to adapt and make increasingly accurate predictions over time.
Creating custom plugins involves developing specialized software components that extend the functionality of a larger application or platform. For users of services like Microsoft Azure, this could mean designing tools that integrate with Azure's cloud capabilities, enhancing AI functionalities or data management. These plugins are specifically tailored to meet unique business needs or improve workflow efficiency, allowing for a more personalized and efficient use of Azure's extensive cloud services, including AI tools and applications. This customization is essential for businesses looking to leverage specific features and optimize their operations uniquely.
Combining prompts and functions involves merging written prompts with specific tasks or operations in computing environments. This integration can enable automation of complex tasks within software applications. For example, in programming with Azure AI on Microsoft Azure, one might combine a text prompt to initiate a sequence with functions that analyze data, generate reports, or engage machine learning models. This approach is crucial in environments like ChatGPT on Microsoft Azure, where dynamic user queries trigger customized functions, enhancing application responsiveness and intelligent output in fields such as Azure AI 102 certification paths.
An AI travel agent is a digital tool that utilizes artificial intelligence to assist users in planning trips, booking flights, and hotels, and providing personalized travel recommendations. Leveraging platforms like OpenAI and Azure, these agents use complex algorithms to analyze vast amounts of data, enabling them to offer customized travel advice and handle inquiries and changes with efficiency. Technologies integrated in solutions, such as ChatGPT on Microsoft Azure, ensure that the AI is continually learning from interactions to improve its accuracy and relevance in travel assistance.
AI solutions involve using advanced algorithms and computing power to enable machines to perform tasks that typically require human intelligence. These tasks include understanding natural language, recognizing patterns, and making decisions. Azure AI, a set of services provided by Microsoft Azure, includes tools and frameworks for implementing AI solutions. By undertaking the Azure AI certification path, professionals can learn about building, training, and deploying AI models on the platform. OpenAI often collaborates with Microsoft Azure, enhancing capabilities in Azure's AI solutions, including ChatGPT on Microsoft Azure. The Azure AI-102 certification specifically focuses on designing and implementing AI apps and agents.
Introduction:
The AZ-2005 course teaches IT professionals to develop AI agents using Azure OpenAI and Semantic Kernel, focusing on automating tasks and natural language processing.
Job Roles/Audience:
In the AZ-2005: Develop AI Agents using Azure OpenAI and Semantic Kernel course, you will learn how to build intelligent applications that automate tasks and perform natural language processing using the Semantic Kernel SDK, within a single day.
Understand the purpose of Semantic Kernel: Learn the fundamental role and capabilities of the Semantic Kernel in building intelligent AI agents.
Master prompting basics: Gain knowledge on how to create effective prompts to interact with AI models proficiently.
Create effective prompts: Develop techniques to enhance the performance and accuracy of your prompts for better AI interactions.
Utilize Semantic Kernel plugins: Understand the functionality of premade plugins and how to incorporate them into your applications.
Develop custom plugins: Learn to design and implement your own plugins to extend the capabilities of the Semantic Kernel.
Implement native function skills: Grasp the concept of native functions within the Semantic Kernel SDK and how to create them.
Combine prompts with native functions: Discover how to integrate prompts and native functions to create more intelligent and dynamic AI responses.
Optimize and use planners: Understand and optimize the use of planners in the Semantic Kernel
