Durée de la formation : 1,72h

As generative AI models have become increasingly popular, enterprises have started to build end-to-end applications to integrate their existing workflows with generative AI. In this course, instructor Kumaran Ponnambalam shows you how to get up and running with integration, performance management, trust, and monitoring to deliver effective and trustworthy generative AI applications at scale. Explore some of the unique characteristics and use cases for generative AI-powered applications in an enterprise setting, including available options, selection criteria, and key deployment considerations for generative AI models. Kumaran covers the basics of evaluating and fine-tuning models as well as patterns and best practices for core application design. By the end of this course, you’ll also be equipped with new skills to manage application performance, maintain safety and trust, and navigate some of the most important ethical and legal challenges of AI.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 1,75h

Cutting-edge artificial intelligence technologies are changing the world. But without proper deployment and management, your applications may never reach their full potential. Worse, they could simply fail or even cause critical errors in your systems. As more organizations are incorporating large language models into their workflows, there's an increasing need for professionals skilled in deploying and monitoring these models effectively, responsibly, and securely in production environments. In this course, learn the advanced techniques and best practices for deploying and monitoring LLMs in production environments. Explore LLM deployment options, handling API limitations, performance monitoring techniques, prompt management, addressing hallucinations, and more. Plus, learn about security and cost considerations, and test your learning with challenges and solutions.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 1,29h

Large language models (LLMs) have taken the AI world by storm. LLMs are behind some of the biggest AI technologies over the last few years, like ChatGPT and GPT-4. In this course, Jonathan Fernandes provides an overview of LLMs suitable for technical learners and non-technical learners alike. Jonathan shows you what LLMs are and what you can do with them, and takes a look under the hood so you can understand why they work the way they do and how they can affect your work. He explains how LLMs are trained and details the components of LLMs, and then takes a look at several different applications of LLMs—including Google’s BERT, GPT-3, PaLM and PaLM 2, ChatGPT and GPT-4, and Llama—and shows you how to compare LLMs using benchmarks.

Topics include:

• Describe the architecture of large language models and their components such as transformers, encoders, and decoders.
• Explain the function and importance of model parameters in neural networks.
• Analyze the efficiency and effectiveness of different language models like GPT-3, BERT, and PaLM in various tasks.
• Interpret the role of scaling laws in optimizing large language models' performance.
• Evaluate the impact of model size and training data volume on the effectiveness of language models.
• Identify the benefits and drawbacks of open community language models compared to proprietary models.
• Compare language model performance using benchmarks like HELM and understand their implications.
• Discuss the trends in reducing inference costs and improving model performance.
• Illustrate the concept of tokenization and context windows in the generation of responses by language models.
• Outline the key challenges and limitations of large language models, including their inability to update in real-time.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 0,56h

Looking to boost your understanding of agentic AI? This course was designed for you. Join instructor and AI expert Zach Kass as he explores the impact of agentic AI on businesses and teams, sharing real-world case studies and insights on practical applications, ethical considerations, and more. Discover how intelligent agents are designed, as well as their historical development, underlying mechanisms, and core functionalities. Along the way, Zack analyzes the current and future role of agentic AI in a wide variety of business roles across different organizational levels and industries. Upon completing this course, you’ll be equipped with a solid understanding of agentic AI and its potential applications across your organization.

Topics include:

• Define agentic AI and distinguish it from other forms of AI.
• Explain the key mechanisms of agentic AI, including perception, decision-making, autonomous action, and learning and adaptation.
• Analyze examples of agentic AI applications in various industries such as autonomous vehicles, healthcare, retail, and finance.
• Evaluate the ethical concerns associated with agentic AI, including undue semantics, blast radius, and the principle of least privilege.
• Describe strategies for integrating agentic AI into business operations, focusing on assessing business needs, building adaptive AI strategies, and engaging and training teams.
• Identify the potential future advancements of agentic AI and the challenges these developments might present.
• Apply knowledge of AI ethics to ensure responsible deployment and use of agentic AI systems.
• Outline the benefits of agentic AI in enhancing efficiency, productivity, and team dynamics within organizations.
• Predict the impact of agentic AI on job roles and workforce dynamics, and formulate approaches to manage workforce displacement.
• Summarize practical techniques for balancing innovation with practicality in AI adoption.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 0,82h

Explore the dynamic landscape of artificial intelligence and gain a strong understanding of both traditional and generative AI. Join instructor and generative AI expert Dr. Marily Nika as she offers an overview of the history of AI—from its conceptual inception to its current state. Discover the differences between traditional AI and generative AI, before diving into constructing effective prompts to enhance the usefulness of AI responses in various contexts. Learn about key technologies including transformer architecture, large language models (LLMs), and real-world applications like chatbots, translators, and agents. Along the way, Marily covers the importance of data quality, expert human contribution, and the back-end technology, such as GPUs, all of which are essential for training AI systems. This course is an ideal fit for tech enthusiasts, data scientists, professionals in tech-driven fields, and anyone looking to leverage AI for personal or professional growth.

Topics include:

• Compare traditional AI systems with generative AI models and describe their unique capabilities and applications.
• Explain what a GPU is and how it leads to overall cost for running AI models.
• Outline the key components of an effective generative AI prompt.
• Identify the ethical considerations in AI development and explain strategies for practicing responsible AI.
• Summarize the impact of data quality on AI outcomes.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 1,06h

Learn how to craft high-impact prompts for generative AI tools. Whether you’re a beginner or have been experimenting with generative AI tools, this course offers a great introduction to the art of prompt engineering. Senior AI engineer Ronnie Sheer guides you through what large language models are and what problems they may be able to solve. Ronnie dives into text generation, starting with a warning to use text generation AI responsibly, then moving on to Copilot, ChatGPT, Gemini, and Claude. He introduces you to the AI generated image landscape, then shows you how to use Dall-E and Midjourney. Plus, Ronnie goes over advanced concepts like fine-tuning your prompts and interacting with language models using an API. This course is part of a Professional Certificate from Microsoft.

Topics include:

• Describe the concept of prompt engineering and its importance in effective interaction with generative AI systems.
• Use generative AI tools like ChatGPT, Google Gemini, Microsoft Copilot, and Anthropic's Claude to generate text and images for different applications.
• Explain the basic components of AI tools, including tokens in the context of generative AI.
• Evaluate the capabilities and limitations of language models to determine which problems can be solved by them.
• Demonstrate awareness of ethical and security considerations in responsible AI use.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 0,83h

From chatbots to predictive analytics, artificial intelligence is transforming the world of work. This course is designed to help you understand key AI concepts and discover how artificial intelligence can benefit your team, organization, products, and services. Instructor Doug Rose breaks down machine learning, predictive AI and generative AI, detailing what they can do and how you can get the most out of them. He also takes a look at legal and ethical issues: Who owns what the machine learned? Can you teach the system values? And more.

Topics include:

• Explain the difference between artificial intelligence and human intelligence.
• Compare artificial neural networks and traditional machine learning.
• Explain the difference between supervised and unsupervised learning.
• Understand why it's crucial to create systems that align with human values.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 0,39h

As AI adoption in organizations evolves, managers need to ensure their teams are using AI responsibly. In this course, instructor Terri Horton shows you how to design and implement responsible AI practices and hold yourself and your team accountable as a manager. Explore the manager's role in responsible AI, in theory and in practice. Get an overview of the guiding principles of ethical AI and responsible AI in management. Terri offers insights on accountability—including data privacy, safety, and how to mitigate bias and risk—before covering key management practices during AI implementation such as decision-making, employee engagement, and psychological safety. Along the way, learn more about AI in action with real-world case examples drawn from business management. This course is part of a Professional Certificate from LinkedIn Learning.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 1,26h

AI is driving innovation and efficiency in the tech industry. As businesses and organizations seek to leverage AI, there's a high demand for skilled professionals who can understand, develop, and ethically implement AI technologies. In this course, award-winning tech innovator and AI/ML leader Kesha Williams helps developers to upskill and merge their existing programming knowledge with AI competencies. Learn about the concept of artificial intelligence and how it revolutionizes traditional programming methodologies. Explore the tools you need to interpret, evaluate, and harness AI technologies effectively. Through Python code examples, get an introduction to the fundamental pillars of AI, including machine learning, neural networks, and computer vision, while addressing ethical considerations for responsible development. By the end of the course, you will be ready to tackle the technological challenges of today and tomorrow with confidence and creativity.

Topics include:

• Upskill existing programming knowledge with AI competencies.
• Interpret and evaluate AI technologies and their applications.
• Gain hands-on experience with building, testing, and debugging AI models.
• Learn practical Python programming skills for developing AI solutions.
• Explore the use of key Python libraries essential for AI development.
• Understand the ethical considerations and best practices in AI development.
• Integrate AI with traditional programming approaches.
• Inspire innovation and creativity in applying AI to solve real-world problems.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 2,45h

Computer scientists are just a small slice of people working in artificial intelligence (AI). Most people working with AI are just like you. They’re professionals, teachers, and students who want to use AI to enhance their products, creativity, and career. AI has been around for over half a century. Despite huge advancements in predictive and generative AI, the core concepts of artificial intelligence are still accessible. This course is designed for project managers, product managers, directors, executives, and students starting a career in AI. First, learn what it means for a system to display “intelligence.” Then, explore the difference between classic predictive AI and newer generative AI. Next, you’ll get an overview of machine learning algorithms, artificial neural networks, foundation models, and deep learning. From the AI curious to the AI careerist, this course will help you get started with intelligent systems. This course is part of a Professional Certificate from Microsoft. This course is part of a Professional Certificate from Microsoft.

Topics include:

• List the distinctions between symbolic systems and machine learning.
• Identify challenges in natural language processing.
• Define the various types of machine learning.
• Explain the importance of algorithms in machine learning.
• Determine conditions in which using artificial intelligence is appropriate.
• Review the differences between artificial intelligence and machine learning that impact business decisions.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

Durée de la formation : 0,65h

In this course, learn to stop feeling anxious about AI and how to effectively integrate AI skills into your daily routine. Instructor Amy Blankson starts by acknowledging common concerns about AI and shows you how to view it as a valuable tool rather than a threat. The course encourages you to explore various AI tools with practical applications, solve real-life problems, and address challenges with structured problem-solving techniques. Additionally, discover ways to infuse empathy into your AI outputs, work more efficiently, and ethically apply AI in your endeavors.

Topics include:

• Identify and acknowledge common anxieties about AI and how to address them.
• Explore and utilize AI tools to solve real-life challenges and improve productivity.
• Apply structured problem-solving techniques to overcome AI-related challenges.
• Integrate ethical guidelines and empathy into AI-generated outputs.
• Develop strategies to seamlessly incorporate AI into everyday routines for maximum efficiency.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation

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

Prerequisites

Before starting this module, you should be familiar with fundamental AI concepts and services in Azure. Consider completing the Get started with artificial intelligence learning path first.

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.

Before starting this learning path, you should already have:

• Familiarity with Azure and the Azure portal.
• Experience programming with C# or Python. If you have no previous programming experience, we recommend you complete the Take your first steps with C# or Take your first steps with Python learning path before starting this one.

In this learning path, discover how Azure AI Document Intelligence solutions can enable you to capture data from typed or hand-written forms. Learn how to build a solution for your custom form types and integrate that solution into an Azure Cognitive Search pipeline. You'll learn how to:

• Design a solution that analyzes your business forms by using Azure AI Document Intelligence.
• Create a solution that analyzes common documents by using Document Intelligence.
• Create a solution that analyses different custom form types by using Document Intelligence.
• Include an Azure AI Document Intelligence service as a custom skill in an Azure AI Search pipeline.

This module provides engineers with the skills to begin building an Azure OpenAI Service solution.

By the end of this module, you'll be able to:

• Create an Azure OpenAI Service resource and understand types of Azure OpenAI base models.
• Use the Azure AI Studio, console, or REST API to deploy a base model and test it in the Studio's playgrounds.
• Generate completions to prompts and begin to manage model parameters.

Prerequisites

• Familiarity with Azure and the Azure portal.
• An understanding of generative AI.
  

Durée de la formation : 1,11h

The next generation of GPT is here, and it’s time to get up to speed. The latest version, GPT-4 Turbo, takes all the core functionalities of GPT-4 and reworks them for more reliable, consistent results and higher performance delivered at speed. Join AI expert Jonathan Fernandes to get a sneak peek at what’s new with the latest release, in this approachable, easy-to-follow course designed for both technical and nontechnical learners. Explore the wide variety of tasks that GPT-4 Turbo can perform with accuracy and ease, as you develop your understanding of how large language models function in interactive natural language processing. Along the way, gather insights from Jonathan on some of the most talked-about updates such as the Assistants API, Code Interpreter, the retrieval tool, function calling, GPTs, and more. Upon completing this course, you’ll have the skills you need to know to get started with GPT-4 Turbo and select the model that’s best for you.

Ce cours n´est disponible qu´en anglais. Si ce n´est pas un problème pour vous, soumettez votre demande.

Demande de formation