Administrative Information

Title Model Compression
Duration 150 min
Module C
Lesson Type Practical
Focus Future AI/Learning – Technical
Topic Model compression


Model Compression, Pruning, Quantization, Knowledge Distillation

Learning Goals

Learner understands how to implement techniques of model compression.
Learner has a grasp the advantages of pruning, quantization, and knowledge distillation.
Learner is familiar with a high-level framework such as TensorFlow.

Expected Preparation

Learning Events to be Completed Before

  • Lecture: Model Compression – Edge Computing

Obligatory for Students

  • Basic understanding of model compression concepts and techniques
  • Basic understanding of how the performance of machine and deep learning models can be evaluated (e.g. accuracy, precision and recall, F score)
  • Knowledge of the Python programming language

Optional for Students

  • Knowledge of the TensorFlow framework

Background for Students

  • Knowledge of machine learning and neural networks theory

Recommended for Teachers

  • Recall knowledge of the TensorFlow framework and Python programming language
  • Provide a practical view on the implementations needed to leverage model compression techniques
  • Propose pop-up quizzes

Instructions for Teachers

  • Give a brief overview of Tensorflow 2.x
  • Use Google Colab as a working Jupyter Notebook for practical application
  • Students must use the indicated time allocated for each task.
  • Task 1 to Task 4 should be completed before the remaining tasks are assigned.

Topics to cover

  • Introduction to tools used and how to make hands dirty in a second (10 mins)
  • [Task 1 – Task 3] Training a model and then? How to apply pruning and quantization to working models and compare performances. (70 mins)
  • [Task 4 – Task 6] When could be knowledge distillation useful? How to distil knowledge from teacher to student. (40 mins)
  • Conclusion, questions and answers (10 mins)


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-ND 4.0

Skip to content