Master Generative AI on Microsoft Azure: Comprehensive In-Depth Training
Elevate Your Skills with Master Generative AI on Microsoft Azure: Comprehensive In-Depth Training
- Advanced Course
- 48 Hours
- 4.7
Course 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.
Objectives of Master Generative AI on Microsoft Azure: Comprehensive In-Depth Training
By The End Of This Course, Participants Will Be Able To:
- Understand The Foundational Concepts And Significance Of Generative AI.
- 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.
- Integrate Various Azure Services To Enhance And Scale Generative AI Solutions For Real-World Applications.
Course Outline
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.
Instructor
ANIL BIDARI
Instructor