This training focuses on the Amazon corner of the cloud universe and aims to give an overview of their most important services and their relevance for Data Science and Machine Learning.
We start the theoretical part of this training by going into the history and background of Cloud Infrastructure in general, and Amazon Web Services in specific. Then, we discuss their solutions for access management, storage, compute, monitoring, etc before moving to Machine Learning services such as Sagemaker (ML), Rekognition (Image and Vision) and Comprehend (NLP) and concluding by mentioning some interesting others.
Having learned about this ecosystem of services we then gain hands-on experience during the lab session, in which we tie multiple components together and eventually train a prediction model for beer preferences based on a dataset of customer reviews.
The training includes theory, demos, and hands-on exercises. After this training you will have gained knowledge about:
- Cloud Infrastructure history and background
- Amazon Web Services background
- Data center regions
- IAM: Access management
- S3: Simple Storage Service
- EC2: Elastic Compute Cloud
- Lambda: Serverless Compute
- Cloudwatch: Monitoring
- API gateway
- Sagemaker: Machine Learning
- Rekognition: Image and Video
- Comprehend: Insights and relationships in text
- Other services such as: Polly (Text to Speech), Transcribe (Speech Recognition) and Translate
- Lab session to get hands-on experience with Amazon Cloud infrastructure