Master Generative AI on AWS Cloud : In-Depth Training
Elevate Your Skills with Master Generative AI on AWS Cloud : In-Depth Training
- Advanced Course
- 48 Hours
- 4.7
Generative AI On AWS Cloud Offers A Comprehensive Exploration Of Generative Artificial Intelligence Within The AWS Ecosystem. Starting With Foundational Knowledge, The Course Progressively Introduces AWS-Specific Tools, Ensuring Participants Gain Hands-On Experience. With Real-World Applications, Interactive Labs, And Expert Guidance, Participants Will Leave With A Solid Grasp Of Generative AI Implementation On AWS.
Course Description
Dive Deep Into The World Of Generative AI With A Specific Focus On AWS Cloud. This Course Will Guide Participants Through The Foundational Concepts Of Generative AI, Introducing Them To AWS’s Unique Tools Like DeepComposer And SageMaker. With Hands-On Labs, Participants Will Experience Real-World Applications, Model Training, And Deployment In The AWS Environment.
Objectives of Master Generative AI on AWS Cloud : In-Depth Training
By The End Of This Course, Participants Will Be Able To:
- Understand The Principles And Applications Of Generative AI.
- Navigate And Utilize AWS Tools And Services Tailored For Generative AI, Including DeepComposer And SageMaker.
- Train, Fine-Tune, And Deploy Generative Models On AWS.
- Address Common Challenges In Generative AI And Apply Best Practices For Optimization.
Course Outline
Registration And Welcome Breakfast
Introduction To Generative AI
– Definition And Significance Of Generative AI.
– Overview Of Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), And Other Generative Models.
– Applications And Potential Of Generative AI.
Introduction To AWS Cloud
– Overview Of Amazon Web Services (AWS).
– Highlight Of AWS’s AI & Machine Learning Services.
Hands-On Lab 1: Setting Up AWS For Generative AI Workloads
– Creating An AWS Account And Setting Up IAM Roles.
– Introduction To Amazon SageMaker And Its Relevance To AI/ML.
– Initial Configuration For Generative AI Workloads.
Morning Break
Dive Into AWS Generative AI Tools
– DeepComposer: Generative AI For Music.
– DeepRacer: Reinforcement Learning Models.
– Overview Of SageMaker’s Capabilities For Custom Generative Models.
Hands-On Lab 2: Exploring Deep Composer
– Setting Up DeepComposer.
– Training A Generative Model For Music Generation.
– Evaluating And Fine-Tuning The Model’s Outputs.
Lunch Break
Advanced Generative AI With SageMaker
– Benefits Of Using SageMaker For Generative AI Tasks.
– Integrating Other AWS Services (Like S3) With SageMaker For Data Management.
– Custom Generative Model Training And Deployment.
Hands-On Lab 3: Training A GAN With SageMaker
– Setting Up The SageMaker Environment.
– Preparing Datasets And Training A GAN Model.
– Visualizing And Interpreting Generated Samples.
Afternoon Break
Challenges And Solutions In Generative AI On AWS
– Addressing Common Issues: Mode Collapse, Training Instability, Etc.
– AWS Tools And Resources For Troubleshooting.
– Best Practices For Model Optimization And Performance.
Hands-On Lab 4: Fine-Tuning And Deployment
– Advanced Techniques For Improving Generative Model Outputs.
– Deploying The Trained Model For Real-Time Generation Tasks.
– Scaling And Managing Generative AI Solutions On AWS.
Q&A, Feedback, And Closing Remarks
End Of Training
This Course Aims To Provide A Comprehensive Insight Into Generative AI On AWS. Ensure To Adjust Pacing Based On The Participants’ Prior Knowledge And Always Incorporate Feedback After Each Hands-On Lab To Gauge Understanding And Make Necessary Adjustments.
Instructor
ANIL BIDARI
Instructor
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