410 Courses

Duration 1 Days 6 CPD hours This course is intended for The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don?t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. Prerequisites Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services. Specifically: Experience using computers and the internet. Interest in use cases for AI applications and machine learning models. A willingness to learn through hands-on exp... 1 - Fundamental AI Concepts Understand machine learning Understand computer vision Understand natural language processing Understand document intelligence and knowledge mining Understand generative AI Challenges and risks with AI Understand Responsible AI 2 - Fundamentals of machine learning What is machine learning? Types of machine learning Regression Binary classification Multiclass classification Clustering Deep learning Azure Machine Learning 3 - Fundamentals of Azure AI services AI services on the Azure platform Create Azure AI service resources Use Azure AI services Understand authentication for Azure AI services 4 - Fundamentals of Computer Vision Images and image processing Machine learning for computer vision Azure AI Vision 5 - Fundamentals of Facial Recognition Understand Face analysis Get started with Face analysis on Azure 6 - Fundamentals of optical character recognition Get started with Vision Studio on Azure 7 - Fundamentals of Text Analysis with the Language Service Understand Text Analytics Get started with text analysis 8 - Fundamentals of question answering with the Language Service Understand question answering Get started with the Language service and Azure Bot Service 9 - Fundamentals of conversational language understanding Describe conversational language understanding Get started with conversational language understanding in Azure 10 - Fundamentals of Azure AI Speech Understand speech recognition and synthesis Get started with speech on Azure 11 - Fundamentals of Azure AI Document Intelligence Explore capabilities of document intelligence Get started with receipt analysis on Azure 12 - Fundamentals of Knowledge Mining with Azure Cognitive Search What is Azure Cognitive Search? Identify elements of a search solution Use a skillset to define an enrichment pipeline Understand indexes Use an indexer to build an index Persist enriched data in a knowledge store Create an index in the Azure portal Query data in an Azure Cognitive Search index 13 - Fundamentals of Generative AI What is generative AI? Large language models What is Azure OpenAI? What are copilots? Improve generative AI responses with prompt engineering 14 - Fundamentals of Azure OpenAI Service What is generative AI Describe Azure OpenAI How to use Azure OpenAI Understand OpenAI's natural language capabilities Understand OpenAI code generation capabilities Understand OpenAI's image generation capabilities Describe Azure OpenAI's access and responsible AI policies 15 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution Additional course details: Nexus Humans AI-900T00 - Microsoft Azure AI Fundamentals training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the AI-900T00 - Microsoft Azure AI Fundamentals course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Thinking about learning more about the ethical use of AI? The BCS Foundation Award; Understanding the Role of Ethics in the Responsible Use of AI, explores the responsibility of organisations and society towards ensuring AI is implemented for the good of others. It considers the potential harm AI may pose, and the safeguards that can be implemented to ensure it is used safely, ethically and for the good of society. You will be encouraged to explore the benefits associated with AI and the potential value it can add towards the continued evolution of humankind if managed well You will learn learn about the impact and level of responsibility of AI in business, an understanding of the need to scale up the impact and responsibility of AI to society, understand the potential harm and safeguards and understand the role of humans in an AI world.

Real-World Use Cases for AI In this session, we'll look at the impact of several recent developments in Artificial Intelligence (AI) including the areas of computer vision, language understanding, and reinforcement learning on our ability to more effectively carry out projects. We'll also dive into real-world use cases where these breakthroughs are being applied to improve our ability to get things done through better communication and collaboration, information processing, and decision making. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Real-World Use Cases for AI In this session, we'll look at the impact of several recent developments in Artificial Intelligence (AI) including the areas of computer vision, language understanding, and reinforcement learning on our ability to more effectively carry out projects. We'll also dive into real-world use cases where these breakthroughs are being applied to improve our ability to get things done through better communication and collaboration, information processing, and decision making. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

This course starts with the basics of data science and gradually moves towards explaining the concepts of machine learning and various data science algorithms.

AI in Project Management: The Next Generation of Project Decision Making Project managers need to make critical project decisions on a daily basis. They are confronted with increasing complexities, high ambiguity and the need to process an exponentially growing amount of data and information in order to make informed and good decisions. This leads to an increasing risk of project failure - meanwhile, the project management industry is already challenged with ongoing low project success rates, caused by often massive failures of projects. Project Data Analytics and Artificial Intelligence (AI) are expected to fill the gap by providing analytical and unbiased capabilities that go beyond human possibilities, towards a data-driven and fact-based decision-making approach. While there is little doubt that AI as a trending technology will disrupt the project management practice and augment today's project management capabilities, AI cannot be seen as just another new tool to make project management more effective. Rather, AI will act as a complement to human intelligence, requiring a collaborative approach and, accordingly, a significant change in project culture and peoples' mindset. Today's project decisions are usually driven by human intuition, experience, leadership, and often do not follow any rational logic. Project decision-makers will be required to abandon such an approach and shift to a data-driven, decision-making approach. This session will provide an overview of the expected changes from AI-driven project management, the resulting impact on project decision making and changes in project culture, and what actions can be taken by project professionals to match their beliefs and behaviours with the new project culture. Learning goals: Gain insights into how AI for project management will significantly change decision-making in projects Gain an understanding of how to transition to a new AI-powered project culture

This course helps you prepare for your CISSP certification. In this course, we will be discussing CISSP? Certification Domain 8 - Software Development Security. This course focuses on how to secure software as we develop it. Domain 8 makes up 11% of the exam questions.

This course will help you prepare for the AI-900 Exam: Microsoft Azure AI Fundamentals. We will cover the complete exam syllabus as updated in April 2021 with sample questions.

This course covers the basic concepts of machine learning (ML) that are crucial for getting started on the journey of becoming a skilled ML developer. You will become familiar with different algorithms and networks, such as supervised, unsupervised, neural networks, Convolutional Neural Network (CNN), and Super-Resolution Convolutional Neural Network (SRCNN), needed to develop effective ML solutions.

This course will help you learn the programming fundamentals with Python 3. It is designed for beginners in Python and is a complete masterclass. This course will help you understand Python GUI, data science, full-stack web development with Django, machine learning, artificial intelligence, Natural Language Processing, and Computer Vision.