AWS Certified AI Practitioner - AIF-C01

This chapter goes into understanding different terms.

This chapter goes into considering machine learning.

This chapter goes into a broad level understanding of the machine learning process.

This chapter goes into working with data.

This chapter goes into the different types of data.

This chapter goes into the different types of machine learning tasks.

This chapter goes into Amazon SageMaker AI.

This chapter goes into a quick intro into the different type of compute options.

This chapter goes into a lab on building an EC2 Instance.

This chapter goes into connecting to an EC2 Instance.

This chapter goes into a note on the costing aspect.

This chapter goes into creating an Amazon SageMaker domain.

This chapter goes into a quick tour into Amazon SageMaker studio.

This chapter goes into the data set.

This chapter goes into the SageMaker Canvas.

This chapter goes into ingesting data.

This chapter goes into getting data insights.

This chapter goes into transforming data.

This chapter goes into training the model.

This chapter goes into making predictions in Amazon Canvas.

This chapter goes into analyzing results.

This chapter goes into the different Machine Learning Algorithms

This chapter goes into ingesting data to build a Regression based model.

This chapter goes into building the regression-based machine learning model

This chapter just provides a note on the model registry and model cards.

This chapter goes into the Amazon SageMaker feature store.

This chapter goes into important points when working with training data.

This chapter goes into using ready-to-use models.

This chapter goes into using Amazon SageMaker jumpstart.

This chapter goes into using Amazon SageMaker clarify.

This chapter goes into using Amazon SageMaker Ground Truth.

This chapter goes into deleting the resources in Amazon SageMaker

This chapter goes into using synthetic data

This chapter goes into the different use cases for machine learning

This chapter goes into the principles of Responsible AI.

This chapter goes into MLOps

This chapter goes into the AWS-Well-Architected Framework of the Machine Learning Lifecycle.

This chapter goes through the inbuilt AWS AI services.

This chapter goes through the Amazon Comprehend service.

This chapter goes through a lab on the Amazon Comprehend service.

This chapter goes through the Amazon Textract service.

This chapter goes through a lab on the Amazon Textract service.

This chapter goes through the Amazon Transcribe service.

This chapter goes through a lab on the Amazon Transcribe service.

This chapter goes through the Amazon Rekognition service.

This chapter goes through a lab on the Amazon Rekognition service.

This chapter goes through the Amazon Polly service.

This chapter goes through a lab on the Amazon Polly service.

This chapter goes through the Amazon Translate service

This chapter goes through a lab on the Amazon Translate service.

This chapter goes through the Amazon Forecast service.

This chapter goes through the Amazon Lex service.

This chapter goes through a lab on the Amazon Lex service.

This chapter goes through the Amazon Personalize service.

This chapter goes through the Amazon Comprehend service.

This chapter goes through the Amazon Kendra service.

This chapter goes into Large Language Models.

This chapter goes into in foundation models.

This chapter goes into Generative AI.

This chapter goes into a look at using ChatGPT.

This chapter goes into an initial look into Anthropic Claude.

This chapter goes into an initial use of Stable Diffusion.

This chapter goes into an initial look into Hugging Face.

This chapter goes into an initial look into Meta Llama.

This chapter goes into what is Amazon Bedrock.

This chapter goes into requesting model access in Amazon Bedrock.

This chapter goes into using the Amazon Titan Model.

This chapter goes into using the Amazon Titan Image Generator.

This chapter goes into using Inference parameters.

This chapter goes into prompt engineering.

This chapter goes into the concept of being clear in your prompts.

This chapter goes into passing data and instructions into prompts.

This chapter goes into prompt templates.

This chapter contains the resources for Prompt Engineering.

This chapter goes into choosing foundation models.

This chapter goes into evaluating foundation models.

This chapter goes into customizing foundation models.

This chapter goes into Amazon Q developer.

This chapter goes into launching an instance with Amazon Aurora.

This chapter goes into connecting to the database.

This chapter goes into the resources for connecting to the database.

This chapter goes into Amazon OpenSearch.

This chapter goes into Retrieval Augmented Generation.

This chapter goes into Amazon Knowledge base and chating with documents.

This chapter goes into an implementation overview of knowledge bases in Amazon Bedrock.

This chapter goes into creating an IAM user.

This chapter goes into the implementation of the knowledge base with Amazon Bedrock.

This chapter goes into the challenges with Generative AI.

This chapter goes into Amazon Bedrock Guardrails.

This chapter goes into a lab on Amazon Guardrails.

This chapter goes into Amazon Bedrock Agents.

This chapter goes into the pricing for Amazon Bedrock.

This chapter goes into Identity and Access Management.

This chapter goes into IAM Users and Groups.

This chapter goes into the AWS Key Management service and Amazon Bedrock.

This chapter goes into Amazon CloudWatch

This chapter goes into Amazon Bedrock and Amazon CloudWatch.

This chapter goes into a Lab on Amazon Bedrock and Amazon CloudWatch.

This chapter goes into AWS CloudTrail.

This chapter goes into Amazon Bedrock and AWS PrivateLink.

This chapter goes into Amazon SageMaker and network isolation.

This chapter goes into Amazon Macie.

This chapter goes into AWS Config.

This chapter goes into AWS Artifact.

This chapter goes into AWS Audit Manager

This chapter goes into the AWS Trusted Advisor service.

This chapter goes into the design of a conversational chatbot.

This chapter goes into securing your Gen-AI applications.

This chapter goes into the Generative AI Security Scoping matrix.

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