Generative AI & Amazon Bedrock Ultimate Hands-on Course 2026

The Chat Playground in AWS Bedrock is a feature that allows you to experiment with chat models provided by Amazon Bedrock. Here’s a brief overview:

1. Experimentation Environment: It provides a console environment where you can test and run inferences on different chat models with various configurations before integrating them into your applications.

2. Prompt Engineering: You can enter prompts, which are sentences or questions that set up a scenario or task for the model. You can also adjust inference parameters to influence the model’s responses.

3. Configuration Options: The playground allows you to modify configurations such as temperature and top-k sampling to see how these changes affect the model’s output.

4. Multimodal Support: If the model supports it, you can include images or documents along with your prompts to get more contextually rich responses.

5. System Prompts: For some models, you can specify system prompts that provide instructions or context about the task or persona the model should adopt during the conversation. This feature is particularly useful for developers and data scientists who want to fine-tune their models and understand how different settings impact the generated responses.

What You’ll Learn:

• Introduction to AWS Bedrock: Get a comprehensive overview of Amazon’s cutting-edge generative AI service.

• Exploring the Image Playground: Learn how to navigate the Image Playground, input text prompts, and adjust parameters to generate high-quality images.

• Model Selection and Usage: Discover the various image generation models available, including Stability AI’s latest models, and understand how to choose the best one for your needs.

• Practical Applications: See how these models can be applied to real-world scenarios such as marketing, advertising, media, and more.

• Advanced Techniques: Dive into advanced features like fine-tuning models and optimizing image outputs for specific use cases.

• Best Practices for Image Generation: Learn tips and tricks to get the most out of your AI-generated images, ensuring they meet your project’s requirements.

Why This Course?

• Expert Instruction: Gain insights from industry professionals with hands-on experience in AI and image generation.

• Interactive Learning: Engage with practical exercises and real-world examples to solidify your understanding.

• Comprehensive Coverage: From setup to advanced techniques, this course covers everything you need to know about AWS Bedrock’s Image Playground.

We will use AWS Gen AI Rekognition service to analyze images from local computer like detect facial expression, type of flower etc.

Amazon Rekognition is a powerful tool for image analysis, leveraging deep learning technology to provide a wide range of capabilities.

Here are some key features and use cases:

1. Key Features: Object and Scene Detection: Identifies objects, scenes, and activities in images. This can be used for cataloging and organizing image libraries.

2. Facial Analysis: Detects faces in images and analyzes attributes such as age, gender, emotions, and more. It can also compare faces to determine if they match.

3. Text Detection: Extracts text from images, including skewed and distorted text, which is useful for reading signs, social media posts, and product packaging.

4. Content Moderation: Detects inappropriate or unsafe content in images, helping to maintain safe and compliant digital environments.

5. Celebrity Recognition: Identifies well-known individuals in images, which can be useful for media and marketing purposes.

6. Custom Labels: Allows you to train custom models to detect specific objects or scenes relevant to your business needs.

What You’ll Learn:

• Introduction to Amazon Bedrock and Lex: Get acquainted with the powerful tools and services that Amazon offers for building generative AI applications.

• Setting Up Your Environment: Learn how to configure your AWS environment and set up the necessary resources for your chatbot.

• Creating Your First Chatbot: Step-by-step instructions on building a basic chatbot, including defining intents, slots, and utterances.

• Integrating Generative AI: Discover how to enhance your chatbot with generative AI capabilities using Amazon Bedrock, enabling more natural and dynamic interactions.

• Advanced Features and Customization: Explore advanced features such as context management, multi-turn conversations, and integrating external data sources.

• Testing and Deployment: Learn best practices for testing your chatbot and deploying it to production environments.

Why This Course?

• Expert Instruction: Benefit from the insights and experience of industry professionals who have successfully implemented AI solutions.

• Hands-On Learning: Engage with practical exercises and real-world examples to solidify your understanding and skills.

• Comprehensive Coverage: From basics to advanced techniques, this course covers everything you need to know to build and deploy a powerful chatbot.

What You’ll Learn:

• Introduction to Sentiment Analysis: Understand the basics of sentiment analysis and its applications in various industries.

• Setting Up Your Environment: Learn how to configure your Python environment and install necessary libraries for sentiment analysis.

• Using Pre-trained Models: Discover how to leverage pre-trained sentiment analysis models to quickly get started with your projects.

• Building Custom Models: Step-by-step instructions on creating your own sentiment analysis models using Generative AI techniques.

• Data Preparation and Processing: Learn how to clean and preprocess text data for accurate sentiment analysis.

• Model Training and Evaluation: Understand the process of training your models and evaluating their performance using real-world datasets.

• Advanced Techniques: Explore advanced topics such as fine-tuning models, handling imbalanced data, and optimizing model performance.

• Practical Applications: See how sentiment analysis can be applied to social media monitoring, customer feedback analysis, and more.

  
  

Why This Course?

• Expert Guidance: Learn from industry experts with hands-on experience in AI and machine learning.

• Interactive Learning: Engage with practical exercises and real-world examples to solidify your understanding.

• Comprehensive Coverage: From basics to advanced techniques, this course covers everything you need to know about sentiment analysis with Python and GenAI.

In this video, we explore how to generate breathtaking images using Amazon Bedrock’s Stable Diffusion model. Discover the power of generative AI and how it can transform simple text prompts into high-quality visuals.

We’ll cover:

1. Introduction to Amazon Bedrock and Stable Diffusion

2. Step-by-Step Guide to Generating Images 

3. Tips and Tricks for Best Results

4, Real-World Applications and Use Cases

Whether you’re a developer, artist, or AI enthusiast, this video will provide you with the knowledge and tools to create amazing AI-generated images. Join us on this creative journey and see how easy it is to bring your ideas to life with Amazon Bedrock.

In this tutorial, we dive deep into the world of social media sentiment analysis using Amazon Comprehend. Learn how to harness the power of AWS to analyze sentiments from various social media platforms and gain valuable insights into public opinion in an end-to-end project.

What You’ll Learn:

1. Setting Up Your Environment: How to store your input files in an Amazon S3 bucket. Using Amazon Comprehend: Step-by-step guide to analyzing social media posts for sentiment.

2. Data Processing: How to organize and store output files, including the corresponding post, social media platform name, and sentiment, in a structured format.

3. Real-World Application: Practical examples and use cases to help you understand the impact of sentiment analysis on business decisions.

This Hands-On Tutorial contains follow along with detailed instructions and code.

In this video, we’ll show you how to convert handwritten text and PDF files into typed text in a .txt file using Amazon Textract. Whether you’re looking to digitize your handwritten notes or extract text from PDFs, Amazon Textract makes it easy and efficient. Follow along as we guide you through each step of the process.

What You’ll Learn:

1. Introduction to Amazon Textract: Understand what Amazon Textract is and how it works.

2. Uploading Your Documents: Step-by-step instructions on how to upload handwritten documents and PDFs to Amazon Textract.

3. Extracting Text: See how to use Textract to extract text from your documents.

4. Saving as .txt File: Learn how to save the extracted text as a .txt file for easy access and editing.

Why Use Amazon Textract?

1. Accuracy: High accuracy in recognizing both printed and handwritten text.

2. Efficiency: Quickly processes large volumes of documents.

3. Versatility: Works with various document types, including PDFs and images.

In this exciting video, we dive deep into the world of automation and data science with a hands-on project using Amazon SageMaker. Whether you’re a seasoned data scientist or just starting out, this tutorial will guide you through the process of creating training and testing datasets from user input data.

What You’ll Learn:

1. Introduction to Amazon SageMaker: Understand the basics and why it’s a game-changer for data scientists. Automating Dataset Creation: Step-by-step guide to automate the creation of training and testing datasets.

2. User Input Integration: Learn how to seamlessly integrate user input data into your datasets.

Best Practices: Tips and tricks to optimize your workflow and ensure high-quality data.