What you'll learn
- Integrate various Azure services to enhance and scale Generative AI solutions for real-world applications.
- Navigate and leverage Microsoft Azure’s AI & Machine Learning services tailored for Generative AI.
- Build, train, and deploy generative models using Azure Machine Learning Studio and Azure Databricks.
- Address common challenges in Generative AI and implement best practices for model optimization.
This course details
- Skill Level : Advance Course
- Study Lecture : 9 Lectures
- Time Duration : 1 Day
- Certificate : Yes
- Training Delivery Mode : Online - Live Instructor Led training
Course Content
- Registration and Welcome Breakfast
Introduction to Generative AI
– Definition and significance of Generative AI.
– An overview of Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and other generative models.
– Potential applications and impact of Generative AI.
Introduction to Microsoft Azure Cloud
– Overview of Microsoft Azure.
– Highlight of Azure’s AI & Machine Learning services.
Hands-on Lab 1: Setting up Azure for Generative AI Workloads
– Initiating an Azure account and setting up resource groups.
– Introduction to Azure Machine Learning service and its relevance to AI/ML.
– Configurations tailored for generative AI workloads.
Morning Break
Dive into Azure Generative AI Tools
– Azure Machine Learning Studio: Model training and deployment.
– Azure Databricks: Distributed data analytics and ML training.
– Azure Cognitive Services: Pre-trained AI services.
Hands-on Lab 2: Building Generative Models with Azure ML Studio
– Setting up the Azure ML environment.
– Training a GAN model for data generation.
– Visualizing and interpreting generated data.
Lunch Break
Advanced Generative AI Techniques in Azure
– Leveraging Azure Databricks for large-scale generative model training.
– Integration of Azure Blob Storage for managing generated data.
– Custom generative model deployment with Azure Kubernetes Service.
Hands-on Lab 3: Distributed Generative AI Training with Azure Databricks
– Setting up a Databricks workspace.
– Parallel training of generative models.
– Optimizing and fine-tuning using distributed resources.
Afternoon Break
Challenges and Solutions in Generative AI on Azure
– Addressing issues like mode collapse, overfitting, etc.
– Azure tools and resources for troubleshooting generative AI challenges.
– Best practices for scalable and efficient generative AI solutions.
Hands-on Lab 4: Deployment and Scaling with Azure Kubernetes Service
– Packaging generative AI models for deployment.
– Setting up Azure Kubernetes clusters.
– Scaling and monitoring generative AI applications.
Q&A, Feedback, and Closing Remarks
End of Training
This course offers a holistic approach to Generative AI within the Microsoft Azure ecosystem. Adjust the pacing and depth based on the participants’ prior knowledge, and always incorporate feedback after each hands-on lab to ensure optimal understanding.
Course Summary
The “Master Generative AI on Microsoft Azure” training provides an immersive experience in the world of Generative AI. Tailored specifically for the Azure platform, participants will delve deep into generative models, leveraging Azure’s powerful tools and services. From understanding the nuances of GANs and VAEs to deploying scalable AI solutions with Azure Kubernetes Service, this course promises both depth and breadth. Expert guidance, combined with hands-on labs, ensures participants leave with actionable skills and a deep understanding of Generative AI’s potential on Azure.
Description
Unveil the transformative capabilities of Generative AI within the Microsoft Azure ecosystem in this comprehensive training course. Participants will embark on a hands-on journey, exploring foundational generative models, Azure-specific AI tools, and real-world applications. With a blend of expert-led lectures and practical labs, learners will gain unmatched expertise in Azure-based Generative AI solutions.
Who this course is for :
- AI enthusiasts and professionals seeking comprehensive expertise in generative AI leveraging Microsoft Azure's robust infrastructure.
- Data scientists and machine learning engineers interested in mastering advanced generative models on the Azure platform.
- Developers and researchers aiming to innovate and deploy scalable generative AI solutions using Microsoft Azure cloud services.
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Instructor
- 4.5 Instructor Rating
- 1,654 Reviews
- 15 Years of Experience
- 9 Courses
Anil Bidari is a versatile trainer and consultant specializing in GitLab, AWS, Azure, Google, DevOps, Jenkins, Kubernetes, Ansible, Docker, Agile, and Machine Learning. His expertise drives successful technology adoption and implementation, benefiting organizations and individuals alike.
Deepika Sharma
Developer