Data analysis in Python — intermediate

Children’s age: 12+

Teacher: Diana Shamsutdinova

The course is for teens who have some experience with Python coding or are willing to catch up very fast in the first month.

First of all, we will continue exploring more datasets, describe them using average, medians, standard deviations and histograms, plot different graphs and diagrams.
Secondly, we will move on to even more exciting areas and try to grasp some ideas of prediction and classification modelling — to see if (and how) a computer program can be ‘trained’ to make reasonable guesses.


Lesson 1-2
What data science can be used for, examples of different problems.
Identifying trends, idea of correlation.
Exploring datasets and trying to see trends with different graphs.

Lesson 3-4
How correlation can be used to predict the future, simple regression examples.

Lesson 5-6
Classification task -what it is? How do we know if a model works or not?
Python: creating a rule-based algorithm and testing its performance.

Lesson 7-8
Classification task: methods used in machine learning

Lesson 9-10
Presenting their projects to the group