AI-102T00 Develop AI solutions in Azure

This three-day, instructor-led course provides IS auditors with the foundational knowledge and background of AI solutions to evaluate their proper governance, design, development, and security to apply their expertise in audit and assurance activities in the enterprise. The course is structured to align with the job practice and features a variety of knowledge check questions, case studies, activities, and discussions designed to apply the concepts to real-life business scenarios.

ISACA Advanced in AI Security ManagementTM (AAISM) validates security management professionals’ ability to demonstrate their expertise in AI. This credential builds upon existing security best practices to enhance expertise and adapt to the evolving AI-driven landscape, ensuring robust protection and a strategic edge.

Artificial intelligence (AI) is not just another technology or process for the business to consider; it is a truly disruptive force, one that delivers an entirely new level of results across business sectors. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI. This course is designed to help business professionals conquer and move beyond the basics of AI to apply AI concepts for the benefit of the business. It will give you the essential knowledge of AI you'll need to steer the business forward.

The AI Fundamentals and AI Hacking 101 ILT teaches students the fundamentals of how AI works under the hood and then how to break it. The first day of the course focuses on the fundamentals of how AI works. Students will learn and perform labs on topics such as: How do neural networks function Training of neural networks The progression of AI for natural language processing Recurrent neural networks (RNN) Large Language Models and Attention Self-Hosting LLMs and interacting with them programmatically The hacking portion of the course focuses on penetration testing AI/LLM based applications such as customer facing chatbots by demonstrating how to detect and exploit common AI vulnerabilities such as: Prompt Injection Sensitive Information Disclosure Improper Output Handling System Prompt Leakage Misinformation Excessive Agency Not only will students learn about these core topics and exploits, but they will also spend hands-on time in a custom-built environment training their own neural networks, tweaking LLMs, exploiting and uncovering vulnerabilities and much more. The online lab features the TCM Vulnerable Chatbot, a customer service chatbot that can interact with customers' tickets and improve its responses via Retrieval Augmented Generation (RAG) using the company's knowledge base.

The AI Hacking 101 ILT teaches students the fundamentals of penetration testing AI/LLM based applications such as customer facing chatbots. The course focuses on demonstrating how to detect and exploit common AI vulnerabilities such as: Prompt Injection Sensitive Information Disclosure Improper Output Handling System Prompt Leakage Misinformation Excessive Agency Not only will students learn about these exploits, but they will also spend hands-on time in a custom-built environment exploiting and uncovering these vulnerabilities. The online lab features the TCM Vulnerable Chatbot, a customer service chatbot that can interact with customers' tickets and improve its responses via Retrieval Augmented Generation (RAG) using the company's knowledge base.

In audio, video, image, gaming, and other media production industries, artificial intelligence (AI) has been a truly disruptive force—enabling a higher level of results in a fraction of the time. The rapid pace at which AI is growing can be overwhelming, and fears of AI tools replacing human workforces are growing. This course is designed to help media professionals understand the basics of AI and leverage the assistive and generative AI tools available to create high-quality productions and production assets. It will give you the essential knowledge of AI you'll need to remain competitive, productive, and relevant in these fast-paced and exciting times. This course is created by Be Licensed in partnership with CertNexus (a division of Logical Operations). It is also designed to assist students in preparing for the CertNexus® AI Technologies in Media (Exam AIM-110) credential.

This course is intended for software developers wanting to build AI infused applications that leverage Microsoft Foundry. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement knowledge connections or tools in your agentic applications. This course also covers multimodal capabilities and understanding of complex content.

Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.

This 1-day course focuses on building intelligent applications that can see, interpret, and reason over images and documents using different multimodal models and agent-based tools. Learners explore how visual and document inputs can be combined with language models to enable structured extraction, analysis, and decision-making workflows. The course emphasizes practical patterns for extracting information, orchestrating tools, and grounding model responses in visual data.

This course prepares learners to design, implement, and operate Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions on Azure. It covers building secure and scalable AI infrastructure, managing the full lifecycle of traditional machine learning models with Azure Machine Learning, and deploying, evaluating, monitoring, and optimizing generative AI applications and agents using Microsoft Foundry. Learners will gain hands-on knowledge of automation, continuous integration and delivery, infrastructure as code, and observability by using tools such as GitHub Actions, Azure CLI, and Bicep. The course emphasizes collaboration with data science and DevOps teams to deliver reliable, production-ready AI systems aligned with modern MLOps and GenAIOps best practices.

Generative Artificial Intelligence (AI) is becoming more accessible through easy-to-use platforms like Azure AI Studio. Learn how to build generative AI applications like custom copilots that use language models and prompt flow to provide value to your users.

This learning path explores how the Azure AI and Azure Machine Learning Services integrations provided by the Azure AI extension for Azure Database for PostgreSQL - Flexible Server can enable you to build AI-powered apps.

Do you have information locked up in structured and unstructured data sources? Using Azure AI Search, you can extract key insights from this data, and enable applications to search and analyze them.

Get more done and unleash your creativity with Microsoft Copilot. In this learning path, you'll explore how to use Microsoft Copilot to help you research, find information, and generate effective content.

Generative Artificial Intelligence (AI) is becoming more functional and accessible, and AI agents are a key component of this evolution. This learning path will help you understand the AI agents, including when to use them and how to build them, using Azure AI Agent Service and Semantic Kernel Agent Framework. By the end of this learning path, you will have the skills needed to develop AI agents on Azure.

This course introduces fundamental concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. It teaches a mix of AI concepts and technology skills that are considered foundational to a successful career implementing AI solutions on Microsoft Azure.

Learn how to use the Semantic Kernel SDK to build intelligent applications that automate tasks and perform natural language processing.

Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands on activities for each topic area.

This course is designed for business users, business leaders, and decision makers who want to understand the transformative potential of generative AI and its impact on their organizations. You'll gain a comprehensive understanding of this technology, learn how it can be leveraged to drive innovation and efficiency, and explore the range of generative AI services available on Google Cloud. By the end of this course, you'll be equipped to make informed decisions about implementing AI solutions.

A major milestone in business automation has been reached—generative AI. Despite its recency, it has already started having a significant impact on our lives. But, the rapid pace at which generative AI is growing can be overwhelming. And, there are so many facets to this field that it can be difficult to know how to use it effectively to improve the business. This course is designed to demystify generative AI for business professionals, as well as to trace its power to actionable, real-world business goals. It will give you the essential knowledge of generative AI you'll need to elevate the organization in these exciting times.

As generative AI becomes more common, the ability to interact with large language models is shifting from niche knowledge to a necessary skill across many different industries and roles. In this course, you will learn the fundamentals of prompting large language models and exploring further techniques for improving the output from large language models.