Administrative information

Title	Data architecture
Duration	60 min
Module	B
Lesson Type	Interactive Session
Focus	Practical - Organisational AI
Topic	Data architecture

Keywords

Data Architecture,Machine Learning pipeline,MLOps,

Learning Goals

To know the basic data architectures in Machine Learning
Pose questions about the most suited data architectures

Expected Preparation

Learning Events to be Completed Before

Tutorial: Data architecture

Obligatory for Students

Data Analysis Process
Machine Learning Models
DevOps
CI/CD

Optional for Students

None.

References and background for students:

DevOps
CI/CD

Recommended for Teachers

Google cloud architecture

Lesson Materials

Slides

The materials of this learning event are available under CC BY-NC-SA 4.0.

Instructions for Teachers

Use the following outline:

Introduction to the discussion
- What are the most diffused architectures for ML Systems?
- What is a typical ML pipeline?
- What is the MLOps?
- How it is possible to automate and orchestrate a ML pipeline?
- How it is possible configure a Continuous Integration/ Continuous Delivery CI/CD system for the ML pipeline using the Cloud?
- Questions and further discussion on topics suggested by students
Discussion
- What are the characteristics of the Tensor Flow eXTended (TFX) architecture?
- How can Cloud support the TFX model?
- How How it is possible to automate and orchestrate the TFX pipeline?
- How it is possible configure a Continuous Integration/ Continuous Delivery CI/CD system for the TFX pipeline?
- Questions and further discussion on topics suggested by students
Conclusions
- Summing up and discussing the lesson outcomes:
  - Main features of an ML System Architecture and of ML pipelines
  - MLOPs
  - Automating and orchestrating a ML pipeline with reference to the TFX model
- Conclusive remarks

Time schedule


Duration (min)	Description	Concepts
20	Introduction to the discussion	ML System Architecture, ML Pipeline
30	Discussion	ML in production examples
10	Summing up and conclusive remarks

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

Acknowledgements

The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.

The materials of this learning event are available under CC BY-NC-SA 4.0

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities