Learning Unit 0: Introduction
In this introductory learning unit, we focus on developing basic data science skills in Python. We explore how datasets are structured, how they are presented and documented, and how Python-based tools can support working with data.
Through three practical tasks, you will become familiar with key aspects of the data science workflow, from examining datasets and their documentation to analysing data and creating simple interactive applications with Streamlit.
Lecture
Videos
Exercises
Task 1 - Basic Data Science
In this learning unit, you will investigate how datasets are typically presented when acquired online. In particular, you will look at what information is provided with the datasets, what is usually included, and what is often missing.
Go the UCI Machine Learning repository and look at the link: dataset submission. Then click on Download and unpack the zip-file. Take a moment to examine the provided files.
Resources for Task 1Task 2 - Dataset Analysis
This reading and reflection task explores questions surrounding ethos and personal project work.
Resources for Task 2Task 3 - Introduction to Streamlit
The goal of this task is to get you familiar with Streamlit, a popular python-based open-source framework for shareable data apps.
Resources for Task 3
