Generative AI Foundations: Advanced Generative AI Techniques for IT
Generative AI
| Intermediate
- 15 videos | 1h 30m 24s
- Includes Assessment
- Earns a Badge
Unlock the transformative potential of advanced generative AI (GenAI) models in site reliability engineering (SRE). This course caters to SRE professionals, IT architects, and those eager to harness the full scope of generative AI in the context of SRE and covers the concepts of advanced generative AI techniques to bolster system reliability, scalability, and efficiency in SRE. In this course, we will begin with an overview of advanced GenAI and SRE. You'll explore how to deploy advanced models from the Azure AI model catalog and transition into testing approaches for applications integrating GenAI. Next, you'll deploy a GenAI-based application to Azure Kubernetes Service (AKS), explore the suitability of GenAI models for SRE, and see which SRE tools incorporate GenAI. With that foundation, you'll experiment with various methods for supporting SRE operations with GenAI including chatbots, implementing a backoff mechanism, evaluating model performance, and configuring log analytics for GenAI models on Azure. Lastly, you'll explore GenAI and SRE advancements, and fine-tune a GenAI model in Azure OpenAI Studio.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Outline the use of advanced generative ai techniques such as generative adversarial networks (gans), variational autoencoders (vaes), and autoregressive models
Identify site reliability engineering (sre) principles and practices that are used to ensure the reliability and availability of software systems
Deploy advanced generative ai models from azure ai model catalog
Employ robust testing and responsible deployment strategies to ensure reliability of advanced generative ai applications
Deploy reliable and scalable apps that integrate generative ai on azure kubernetes service (aks)
Assess the suitability of advanced generative ai models for enhancing sre practices using azure
Support sre operations by providing an ai chatbot customized to answer questions regarding sre best practices -
Identify sre tools and platforms that incorporate advanced generative ai capabilities for enhanced incident management and monitoring
Improve site reliability by implementing a backoff mechanism to avoid rate limiting errors in generative ai applications
Evaluate a generative ai model using azure ai studio’s evaluation feature
Provide an overview of generative ai and sre advancements with a focus on how azure-based technologies can adapt and innovate in the space
Configure a log analytics workspace and diagnostics settings to enable analytics for generative ai resources
Optimize and fine-tune advanced generative ai models
Summarize the key concepts covered in this course
IN THIS COURSE
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1m 37sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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5m 49sAfter completing this video, you will be able to outline the use of advanced generative AI techniques such as generative adversarial networks (GANs), variational autoencoders (VAEs), and autoregressive models. FREE ACCESS
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3. Site Reliability Engineering (SRE)5m 33sUpon completion of this video, you will be able to identify site reliability engineering (SRE) principles and practices that are used to ensure the reliability and availability of software systems. FREE ACCESS
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4. Deploying Advanced Generative AI Models5m 53sLearn how to deploy advanced generative AI models from Azure AI model catalog. FREE ACCESS
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5. Testing Generative AI Application Reliability7m 16sIn this video, find out how to employ robust testing and responsible deployment strategies to ensure reliability of advanced generative AI applications. FREE ACCESS
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6. Deploying Reliable Generative AI Applications10m 56sDiscover how to deploy reliable and scalable apps that integrate generative AI on Azure Kubernetes Service (AKS). FREE ACCESS
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7. Suitability of Advanced Generative AI Models for SRE9m 6sIn this video, you will learn how to assess the suitability of advanced generative AI models for enhancing SRE practices using Azure. FREE ACCESS
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8. Supporting SRE Operations with AI Chatbots8m 57sDuring this video, discover how to support SRE operations by providing an AI chatbot customized to answer questions regarding SRE best practices. FREE ACCESS
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9. SRE Tools and Platforms with Advanced Generative AI4m 20sAfter completing this video, you will be able to identify SRE tools and platforms that incorporate advanced generative AI capabilities for enhanced incident management and monitoring. FREE ACCESS
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10. Improving Reliability of Generative AI Applications5m 58sFind out how to improve site reliability by implementing a backoff mechanism to avoid rate-limiting errors in generative AI applications. FREE ACCESS
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11. Evaluating Generative AI Model Performance6m 38sLearn how to evaluate a generative AI model using Azure AI Studio’s evaluation feature. FREE ACCESS
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12. Generative AI and SRE Advancements5m 59sUpon completion of this video, you will be able to provide an overview of generative AI and SRE advancements with a focus on how Azure-based technologies can adapt and innovate in the space. FREE ACCESS
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13. Configuring Log Analytics for Generative AI Resources6m 25sIn this video, find out how to configure a log analytics workspace and diagnostics settings to enable analytics for generative AI resources. FREE ACCESS
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14. Optimization of Advanced Generative AI Models4m 56sDiscover how to optimize and fine-tune advanced generative AI models. FREE ACCESS
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15. Course Summary1m 1sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
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