Lab 11. Project / Case Study

This week is for working on the laboratory project and preparing the final presentation.


Select an algorithm and a dataset to make a presentation / case study of 10-25 slides. The combination of an algorithm and a dataset has to be unique for each student.

The list of algorithms can be found on MS Teams / Laboratory channel

An algorithm can be selected by at most 3 students.

  • If you choose an algorithm that was used in the Laboratory, you will have to use another dataset.
  • If you choose another algorithm, you can also use a dataset from the Laboratory.

The structure of the presentation should be as follows:


Describe the context of your case study. Introduce the algorithm and possible applications in real world scenarios.


Describe the algorithm in more detail (text, pseudocode, flowcharts), with use cases and methods for working with real data sets.

Case Study

Describe the selected data set(s) and the implementation of the algorithm in Python. Present the results (text and visual output) and your observations.


Describe the outcome of the case study and applications in real world scenarios in broader terms.


Present the resources used for the case study: algorithm, data sets and other references


Algorithms and Libraries

You can refer to the Laboratories or use any other implementation in Python.

Useful libraries for data science in Python include:

Machine Learning

Deep Learning

Data Processing


Examples of applications can be found on:


You can use any open dataset. Some common sources include:

Dataset aggregators for Machine Learning projects

Open Datasets

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