The Generative AI Cloud Odyssey: Exploring AWS, Azure, and GC

The Generative AI Cloud Odyssey: Exploring AWS, Azure, and GCP. 

Combining cloud computing and artificial intelligence has enabled groundbreaking progress. Organizations can fully unleash the potential of advanced generative AI models by utilizing the powerful cloud platforms of AWS, Google Cloud Platform, and Azure. These cloud service providers’ vast computational resources, existing data, and artificial intelligence and machine learning tools allow researchers and developers to explore deep learning, neural networks, and natural language processing, resulting in highly advanced generative AI solutions.
This LearningKit gives a strong basic understanding of Generative AI Concepts and Models, with extra focus on Large Language Models (LLMs), before exploring Generative AI on the different Cloud platforms.

The LearningKit is divided into the following four tracks:

• Track 1: Generative AI for Innovation and Business Value
• Track 2: Exploring Generative AI on AWS
• Track 3: Exploring Generative AI on Azure
• Track 4: Exploring Generative AI on GCP

This LearningKit with more than 30 hours of learning is divided into three tracks:

Course content

Track 1: Generative AI for Innovation and Business Value

E-learning courses:

Generative AI: An Introduction to Generative AI Concepts

Course: 2 Hours, 38 Minutes

• Course Overview
• What Is Generative Artificial Intelligence (AI)
• Generative AI vs. Other AI Approaches
• Fundamental Concepts in Generative AI
• The Generative AI Ecosystem
• Generative Models: GANs and VAEs
• Workflow of Training Generative Models
• Strengths and Limitations of Generative Models
• Generative AI: Prospects and Challenges
• Synthetic Data with Generative AI
• Generating Synthetic Data with Generative AI
• Ethical Considerations in Generative AI
• Generative Model Evaluation
• Real-world Applications of Generative AI
• The Impact of Generative AI on Society and Creativity
• Responsible AI in the Generative Era
• Course Summary

Generative AI: Generative Modeling Foundations

Course: 1 Hour, 58 Minutes

• Course Overview
• Introduction to Training Generative Models
• Bayesian Statistics and Examples
• Generative vs. Discriminative Models
• Framework of Generative Modeling
• Generative Model Types
• Deep Dive into Variational Autoencoders (VAEs)
• Generative Adversarial Networks (GANs) Unveiled
• Autoregressive Models Explored
• Introduction to Normalizing Flow Models
• Energy-based Models: A Primer
• Diffusion Models
• Generative Model Evaluation
• Course Summary

Generative AI: Getting Started with Large Language Models (LLMs)

Course: 1 Hour, 36 Minutes

• Course Overview
• Large Language Models (LLMs)
• Architecture of LLMs
• Pre-training Approaches
• Impact of Data on Performance
• Fine-tuning LLMs
• Ethical Implications of LLMs
• LLMs and Text Generation
• Challenges in Large Model Training
• Applications of LLMs
• Bias Mitigation in LLMs
• Research and Advancements in LLMs
• Course Summary

Generative AI: Exploring the Depths of Large Language Models in Generative AI

Course: 1 Hour, 48 Minutes

• Course Overview
• Analyzing the Architectural Components in Large Language Models (LLMs)
• Evaluating the Impact of Training Approaches
• Implementing Fine-tuning Techniques
• Analyzing Challenges in LLMs
• Controllable Text Generation
• General Purpose vs. Domain-specific LLMs
• Executing Domain-specific Fine-tuning
• Multimodal Generative AI
• Multimodal Implementation
• Handling Bias in LLMs
• Optimizing LLM Architectures
• Emerging Trends in LLMs
• Course Summary

Generative AI: Leveraging Generative AI for Business

Course: 1 Hour, 38 Minutes

• Course Overview
• Generative AI for Business
• Business Challenges and Opportunities with Generative AI
• Ethical Implications of Business AI
• Generative AI Success Stories
• Business Impact of Generative AI
• Data Management for AI in Business
• Techniques of Generative AI for Business
• Human-AI Collaboration in Business
• Risks and Mitigations of Business AI
• Legal Aspects of AI in Business
• Return on Investment (ROI) of Generative AI
• Strategic AI Roadmap for Businesses
• Course Summary

Assessment:

• Final Exam: Demystifying Generative AI

Track 2: Exploring Generative AI on AWS

E-learning courses:

Generative AI on AWS: Generative AI on AWS: Getting Started

Course: 1 Hour, 10 Minutes

• Course Overview
• Generative Artificial Intelligence (AI) Principles in an AWS Context
• Advantages of Using AWS for Generative AI
• Foundational Models in AWS and Their Popularity
• AI Startup Foundational Models
• How Foundational Models Operate
• Power of Generative Models by Foundational Models
• AWS Generative AI Services
• AI Services vs. Generative AI Services on AWS
• AWS Generative AI Service Deep Dive
• Generative AI Uses Cases
• Working with Generative AI on AWS
• Course Summary

Generative AI on AWS: Building GenAI Models with Amazon SageMaker

Course: 1 Hour, 36 Minutes

• Course Overview1
• Fundamental Concepts of Generative Models
• Types of Generative Models: GANs and VAEs
• Comparing Generative Model Architectures
• Designing GANs with Amazon SageMaker
• Performing Data Preprocessing for Generative Models in SageMaker
• Training Generative Models with SageMaker Algorithms
• Executing Distributed Training of Generative Models in SageMaker
• Optimizing and Fine-tuning Generative Models in SageMaker
• Applying Transfer Learning for Generative Models in Specific Domains
• Evaluating Generated Content Quality and Diversity
• Deploying Generative Models in SageMaker for Real-time Inference
• Monitoring Generative Models in SageMaker
• Course Summary

Generative AI on AWS: Building GenAI Models with Amazon Bedrock

Course: 1 Hour, 6 Minutes

• Course Overview
• Amazon Bedrock
• Generative AI Models with Amazon Bedrock
• Benefits of Amazon Bedrock
• Amazon Bedrock API
• Using the Amazon Bedrock Console
• Developing a Generative AI Model
• Evaluating a Generative AI project
• Designing a Business Application Using Amazon Bedrock
• Amazon Bedrock Strengths and Weaknesses
• Course Summary

Generative AI on AWS: Generating Code with Amazon CodeWhisperer

Course: 1 Hour, 8 Minutes

• Course Overview
• Artificial Intelligence (AI) Code Generation Explained
• Amazon CodeWhisperer
• Code Generation with CodeWhisperer
• CodeWhisperer Use Cases
• Key Features of CodeWhisperer
• Setting Up CodeWhisperer
• Getting Started with CodeWhisperer
• Code Suggestions
• Configuring Security Scans
• Optimizing Software Development with CodeWhisperer
• CodeWhisperer Best Practices
• Course Summary

Generative AI on AWS: Generating Speech with Amazon Polly

Course: 1 Hour, 25 Minutes

• Course Overview
• Amazon Polly
• Key Features of Amazon Polly
• Ways to Use Amazon Polly
• Trying out Amazon Polly
• Getting Started with Amazon Polly
• Installing and Configuring Amazon Polly for Windows
• Synthesizing Speech Programmatically
• Working with Amazon Polly Security
• Exploring Amazon Polly Voice Options
• Neural TTS
• Using Speech Marks
• Implementing API Actions Using Amazon Polly
• Amazon Polly Best Practices
• Data Types
• Course Summary

Generative AI on AWS: Creating Intelligent Chatbots

Course: 1 Hour, 25 Minutes

• Course Overview
• Intelligent Chatbots
• Amazon Lex
• Key Features of Amazon Lex
• Ways to Use Amazon Lex
• Getting Started with Amazon Lex
• Building Bots
• Deploying Bots
• Integrating Amazon Lex and Amazon Polly
• Filtering Based on User Context
• Using Responses
• Integration with Amazon Lex
• Best Practices for Using Intelligent Chatbots
• Chatbot Performance Evaluation
• Course Summary

Generative AI on AWS: Deploying & Managing GenAI Services on AWS

Course: 1 Hour, 6 Minutes

• Course Overview
• Generative Artificial Intelligence (AI) Services
• AWS Machine Learning Solutions
• Generative AI Deployment Services in AWS
• Best Practices for Using Generative AI
• Preparing for Generative AI Deployment on AWS
• Scalable and Highly Available Architecture
• Pretrained AWS AI Services
• Security, Compliance, and Vulnerability Management
• New Tools for AWS Generative AI
• Intelligent Document Processing
• Course Summary

Assessment:

• Final Exam: Generative AI on AWS

Track 3: Exploring Generative AI on Azure

E-learning courses:

Generative AI on Azure: Introduction to Generative AI on Azure

Course: 1 Hour, 25 Minutes

• Course Overview
• Understanding Generative Artificial Intelligence (AI) and How it Works
• Types of Generative AI Models
• Azure Services for Generative AI
• Advantages of Generative AI with Microsoft Azure
• Azure OpenAI Service
• Azure Bot Service
• Azure Machine Learning
• Privacy and Policy Considerations for Generative AI Application Development
• Chatbot Creation with Azure Generative AI
• Personalized Marketing Content with Azure Generative AI
• New Product Development with Azure Generative AI
• How Generative AI Models are Trained and Tuned
• Course Summary

Generative AI on Azure: Generative AI with Azure OpenAI

Course: 1 Hour

• Course Overview
• Introduction to Azure OpenAI Service
• Azure OpenAI Service Models
• Practical Uses for Azure OpenAI Service
• Artificial Intelligence (AI) Content Generation Principles
• Integration with Azure OpenAI
• Text and Question Answering with Azure OpenAI
• Azure OpenAI vs. Other Generative AI Services
• Azure OpenAI Pricing
• Limitations of Azure OpenAI
• The Future for Azure OpenAI
• Course Summary

Deep Dive Into Generative AI with Azure OpenAI

Course: 2 Hours

• Course Overview
• Introduction to Azure OpenAI Architecture
• Getting Started with Azure OpenAI
• Deploying Models with Azure OpenAI
• Working with Azure OpenAI Studio Playground
• Exploring Azure OpenAI Studio Management Features
• Building a Custom App
• Fine-tuning Azure OpenAI Models
• Generating Text
• Performing Language Translation
• Creating Assistants
• Generating Images
• Azure OpenAI Monitoring and Troubleshooting
• Integrating with Azure OpenAI Service
• Azure AI Search
• Integrating OpenAI and Azure AI Search
• Configuring Azure OpenAI for Privacy and Compliance
• Quotas and Collaboration using Azure OpenAI Service
• Course Summary

Generative AI & the Azure Bot AI Service

Course: 1 Hour, 16 Minutes

• Course Overview
• Azure Bot Service
• Generative AI Models and Bots
• The Ethics of Generative AI-driven Bots
• Azure Cognitive Services and Scaling
• Monitoring Azure Bots
• Data Security and Azure Bot Service
• Azure AI Bot Service Cost Monitoring
• Using a Low-code Solution to Build an AI Bot
• Training and Deploying AI Models for CLU Projects
• Integrating an AI Language Resource with AI Search
• Creating a Custom Question Answering Bot
• Monitoring and Troubleshooting Azure Bots
• Course Summary

Assessment:

• Final Exam: Generative AI on Azure

Track 4: Exploring Generative AI on GCP

E-learning courses:

Generative AI on GCP: An Introduction

Course: 1 Hour, 57 Minutes

• Course Overview
• Introduction to Generative Artificial Intelligence (AI)
• Google Cloud Platform (GCP) and Generative AI
• Advantages of Generative AI with GCP
• Generative AI Challenges on GCP1
• GCP Machine Learning
• The Generative AI Life Cycle
• Image Generation and Natural Language Processing (NLP)
• Generating Images with GCP
• Working with Natural Language Processing in GCP
• Best Practices for Developing Generative AI
• GCP Privacy, Security, and Compliance
• Monitoring and Logging with GCP
• Generative AI Use Cases
• Course Summary

Generative AI on GCP: Empowering Machine Language Workflows with Vertex AI

Course: 1 Hour, 39 Minutes

• Course Overview
• Introduction to Vertex AI
• Vertex AI Features
• Deploying a Model with Vertex AI
• Simplifying End-to-end Workflow with Vertex AI
• Pros and Cons of Vertex AI
• How Vertex AI Accelerates Development and Deployment
• Selecting, Training, and Evaluating Models
• Integrating Vertex AI with AI Frameworks
• Data Preparation, Feature Engineering, and Model Evaluation
• Vertex AI Success Stories
• Course Summary

Generative AI on GCP: Harnessing Generative AI with Vertex AI

Course: 1 Hour, 14 Minutes

• Course Overview
• Generative AI Support in Vertex AI
• Vertex AI Generative AI Models
• Generative AI Studio
• Working with the Vertex AI API
• Using Vertex AI Model Garden
• Working with Models in Model Garden
• Creating Custom Models in Vertex AI
• Responsible AI with Safety Filters
• Vertex AI Search and Conversation
• Using Vertex AI Search and Conversation
• Course Summary

Generative AI on GCP: Deep Dive Into Generative AI Studio

Course: 1 Hour, 37 Minutes

• Course Overview
• Generative AI Prompt Design
• Using Generative AI Prompt Samples
• Training a Model with Generative AI Studio
• Tuning a Language Model
• Evaluating Model Performance
• Google Cloud Platform (GCP) Generative AI Deployment
• Deploying a Model
• How Organizations Use GCP Generative AI
• Converting Speech to Text
• Prototyping Language Applications
• Course Summary

Generative AI on GCP: Building Generative AI-powered Apps in GCP

Course: 1 Hour, 17 Minutes

• Course Overview
• Plan and Build a Generative Artificial Intelligence (AI) Model
• Setting up a Python Environment
• Loading Training Data
• Designing and Building a Generator
• Designing and Building Discriminator
• Building a Training Loop
• Running a Training Loop
• Dockerizing the Training Script
• Running a Docker Container on Vertex AI
• Deploying a Finished Model to an API Endpoint
• Course Summary

Assessment:

• Final Exam: Generative AI on GCP

Specificaties

Taal: Engels
Kwalificaties van de Instructeur: Gecertificeerd
Cursusformaat en Lengte: Lesvideo's met ondertiteling, interactieve elementen en opdrachten en testen
Lesduur: 30:03 uur
Assesments: De assessment test uw kennis en toepassingsvaardigheden van de onderwerpen uit het leertraject. Deze is 365 dagen beschikbaar na activering.
Online Virtuele labs: Ontvang 12 maanden toegang tot virtuele labs die overeenkomen met de traditionele cursusconfiguratie. Actief voor 365 dagen na activering, beschikbaarheid varieert per Training.
Online mentor: U heeft 24/7 toegang tot een online mentor voor al uw specifieke technische vragen over het studieonderwerp. De online mentor is 365 dagen beschikbaar na activering, afhankelijk van de gekozen Learning Kit.
Voortgangsbewaking: Ja
Toegang tot Materiaal: 365 dagen
Technische Vereisten: Computer of mobiel apparaat, Stabiele internetverbindingen Webbrowserzoals Chrome, Firefox, Safari of Edge.
Support of Ondersteuning: Helpdesk en online kennisbank 24/7
Certificering: Certificaat van deelname in PDF formaat
Prijs en Kosten: Cursusprijs zonder extra kosten
Annuleringsbeleid en Geld-Terug-Garantie: Wij beoordelen dit per situatie
Award Winning E-learning: Ja

Tip! Zorg voor een rustige leeromgeving, tijd en motivatie, audioapparatuur zoals een koptelefoon of luidsprekers voor audio, accountinformatie zoals inloggegevens voor toegang tot het e-learning platform.