Cloud Enabled SG

Master AI Programming with Cloud Enabled

4.2
4.2/5
Price :

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Category :
Management
Consultant 1
Anil Bidari

Chief Consultant

At Cloud Enabled, our AI Programming Course equips you with hands-on experience in building AI models, developing machine learning algorithms, and deploying intelligent solutions using Python, TensorFlow, and more.

Ai Programming Course
OVERVIEW :
AI Programming Course – Training Modes

🎓 Instructor-Led Online Training – Live sessions with real-time Q&A.
🏢 Corporate AI Programming Training – Custom training for businesses and teams.

🚀 Choose your learning mode & get started! Enroll Now!

Why Cloud Enabled for AI Programming Training?

  • Leading AI Training Institute in Singapore.
  • Expert AI & ML Instructors.
  • Hands-On AI Development with Real-World Applications.
  • Industry-Recognized AI Certification.
  • Latest AI Programming Trends & Tools.
Modes of Learning – Complete Curriculum

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.

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.

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.

 

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.

  • Interactive instructor-led sessions
  • Hands-on learning experience

Let's Enroll Our Course !!

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