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Time | Topic | Description |
---|---|---|
9:00 AM – 9:15 AM | Welcome and Introductions | |
9:15 AM – 10:00 AM | Module 1: Introduction to AI\ML Services in AWS | The goal of this module is to provide an overview and introduction to AI\Ml services that are currently offered by AWS. |
10:00 AM – 11:00 AM | Module 2: Amazon Lex Lab | Within this lab, participants will have the opportunity to create a Chatbot leveraging Amazon Lex. |
11:00 AM – 11:15 AM | Break | |
11:15 AM – 12:00 AM | Module 3: Deep Dive into Amazon Rekognition + Demo | We will be review the Amazon Rekognition service in greater detail and demonstrating a demo leveraging AWS DeepLens. |
12:00PM – 1:00 PM | Lunch | |
1:00 PM – 1:30 PM | Module 4: Deep Dive into Amazon SageMaker | In this module, we will be diving deeper into what is Amazon SageMaker and potential use cases for it. |
1:30 PM – 2:00 PM | Module 5: Amazon SageMaker Lab | Within this lab, participants will create a Jupyter Notebook leveraging Amazon SageMaker and build a recommendation engine. |
Materials
- Amazon Lex Lab
View file name Lab: Module 2 - Lex Chatbot Lab.docxheight 250 - SageMaker Lab SageMaker Lab: https://aws.amazon.com/getting-started/tutorials/build-train-deploy-machine-learning-model-sagemaker/?trk=gs_card
- Presentation: https://cornell.box.com/s/l2ywhmln14h36b6qzkbvam1n8xveg2oq