Day-1
1. Introduction
- Introduction to course/aws
- Generative AI Fundamentals
- Case Study: Generative AI
- Understanding AI/ ML / DL / GenAI
2. Building Application with AI
- Introduction to AI
- Strong AI vs Weak AI
- Benefits of using AI
- Limitations & General Use cases
- AWS Rekognition for Image recognition
- Case Study
LAB- Using lambda to interact with Amazon Recognition/Textract service using boto3
3. Introduction to ML
- Introduction to Machine Learning
- ML in Action
- What is model?
- Categories of Machine Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- ML Pipeline on AWS
- AWS Machine Learning Stack
- AW ML Use cases
- Case Study
4. Amazon SageMaker
- Introduction to Amazon SageMaker
- What Amazon SageMaker can do?
- Case Study
- Amazon SageMaker GroundTruth
- Amazon SageMaker Notebooks
- SageMaker Algorithms
Demo: Labeling data using GroundTruth
Lab - Launching SageMaker Notebook instance
Day-2
1. Problem Formulation
- ML Problem Formulation
- Understanding Data
2. Data Processing
- Data Collection
- Integrating Data
- Using DataLake Architecture
- Data Processing using Amazon EMR, Glue, DataBrew, Python libraries - Pandas, Numpy, MatplotLib/Seaborn etc
- Cleaning Dirty Data
- Understanding outliers
- Amazon Macie
Lab - cleaning data using Sagemaker notebook with pandas and matplotlib
Day-3
1. Model Training
- Choosing right ML Model
- Splitting data and cross-validation
- Model Training
- Model Evaluation
- Feature Engineering
- Model Deployment
Lab - using SageMaker to train Model & deploy
2. Introduction to Deep Learning
- Introduction to Deep Learning
- Using Artificial Neural Networks (ANN)
- Deep Neural Networks (DNNs)
- Deep Learning vs Machine Learning
- Application
- Deep Learning on AWS
3. Generative AI
- Introduction to GenAI,
- Generative AI vs Deep Learning
- Types of Generative AI
- Generative Adversarial Network (GAN)
- Recurrent Neural Network (RNNs)
- Long Short Term Memory (LSTM)
- Transformer
- Generative AI on AWS
- Need of Generative AI
Demo/Lab - Creating bot with Amazon Lex
Day-4
1. Amazon Sagemaker Jumpstart, Amazon Bedrock, Amazon Titan, AWS CodeWhisperer
- Foundation Model
- Build your own Foundation Model
- Amazon Titan Foundation Model
- Large Language Model (LLMs)
- RAG/LangChain
- Fine Tuning
- Stable difusion
- Amazon SageMaker Jumpstart
- Amazon Bedrock
- Amazon CodeWhisperer
- Case Study
Demo/Lab - Using Amazon Bedrock
Demo: Fine tuning Bedrock Model
Lab - Building GenAI using predefined FM models
Lab- Using Bedrock agents
2. Scaling & deploying production scale GenAI on AWS
- Scaling & deploying production scale GenAI on AWS
Demo : building app using SageMaker jumpstart fm models
3. Securing GenAI Applications
- Threats to AI Applications
- Single sign-on with SAML, OpenID Connect
- Restricting Access to Sensitive Data
- Monitoring with GuardDuty
- Monitoring with Macie
- Other Security Best Practices
- Benefits, Risk of using GenAI