Duration: 5 days – 35 hrs
Overview
The Artificial Intelligence using AWS Training Course is designed to provide participants with a comprehensive understanding of artificial intelligence (AI) concepts and how to leverage AWS services for developing AI-powered applications. This course combines theoretical knowledge with hands-on exercises to equip participants with the skills needed to design, implement, and deploy AI solutions using AWS AI services.
Objectives
- Understand fundamental concepts and principles of artificial intelligence and machine learning.
- Explore the AI services provided by AWS and their applications.
- Design and implement machine learning models using AWS services such as Amazon SageMaker and Amazon Rekognition.
- Learn how to use natural language processing (NLP) techniques with AWS services like Amazon Comprehend and Amazon Lex.
- Build AI-powered applications using AWS services for computer vision and speech recognition.
- Integrate AI models with other AWS services and APIs for enhanced functionality.
- Gain hands-on experience in training, evaluating, and deploying AI models on AWS.
- Understand best practices for data preparation, model training, and performance optimization.
- Explore ethical considerations and challenges in AI development on AWS.
Audience
- Developers interested in exploring artificial intelligence and machine learning with AWS
- Data scientists looking to apply AI techniques using AWS services
- IT professionals involved in AI projects and applications
- Technical individuals seeking to enhance their skills in AI development on AWS
Pre- requisites
- Basic knowledge of machine learning concepts and familiarity with AWS services is recommended.
Course Content
Day 1: Introduction to Artificial Intelligence and AWS
- Introduction to Artificial Intelligence (AI) and its applications
- Overview of AWS (Amazon Web Services) and its AI services
- Setting up an AWS account and accessing the AWS Management Console
- Introduction to AWS AI services: Amazon Rekognition, Amazon Polly, Amazon Lex, and Amazon Comprehend
- Hands-on activity: Setting up an AWS environment and exploring AI services
Day 2: Machine Learning on AWS
- Introduction to Machine Learning (ML) and its concepts
- Overview of AWS Machine Learning services: Amazon SageMaker and Amazon Forecast
- Data preparation and exploration on AWS
- Building and training ML models using AWS SageMaker
- Model deployment and hosting on AWS
- Hands-on activity: Building and deploying a machine learning model using AWS SageMaker
Day 3: Natural Language Processing (NLP) with AWS
- Introduction to Natural Language Processing (NLP) and its applications
- AWS services for NLP: Amazon Comprehend and Amazon Transcribe
- Text preprocessing and feature extraction using AWS services
- Sentiment analysis and text classification with AWS Comprehend
- Speech-to-text transcription using AWS Transcribe
- Hands-on activity: Performing sentiment analysis and speech-to-text transcription with AWS NLP services
Day 4: Computer Vision with AWS
- Introduction to Computer Vision and its applications
- AWS services for Computer Vision: Amazon Rekognition and Amazon Textract
- Image and video analysis using AWS Rekognition
- Object detection and facial recognition with AWS Rekognition
- Extracting text from images and documents using AWS Textract
- Hands-on activity: Implementing image analysis and text extraction using AWS Computer Vision services
Day 5: Advanced AI on AWS
- Introduction to advanced AI techniques
- AWS services for advanced AI: Amazon Polly and Amazon Lex
- Building conversational interfaces with AWS Lex
- Text-to-speech synthesis using AWS Polly
- Integration of AI services into applications using AWS SDKs
- Hands-on activity: Creating a chatbot and implementing text-to-speech functionality using AWS AI services
- Note: The course outline provided above is a general framework for a 5-day course on Artificial Intelligence using AWS. The actual content, duration, and hands-on activities can be customized based on the specific needs and level of expertise of the participants. It is important to ensure that participants have access to an AWS account with appropriate permissions to fully benefit from the hands-on activities.
